Explore Courses
Liverpool Business SchoolLiverpool Business SchoolMBA by Liverpool Business School
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA (Master of Business Administration)
  • 15 Months
Popular
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Business Administration (MBA)
  • 12 Months
New
Birla Institute of Management Technology Birla Institute of Management Technology Post Graduate Diploma in Management (BIMTECH)
  • 24 Months
Liverpool John Moores UniversityLiverpool John Moores UniversityMS in Data Science
  • 18 Months
Popular
IIIT BangaloreIIIT BangalorePost Graduate Programme in Data Science & AI (Executive)
  • 12 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with concentration in Generative AI
  • 3 Years
upGradupGradData Science Bootcamp with AI
  • 6 Months
New
University of MarylandIIIT BangalorePost Graduate Certificate in Data Science & AI (Executive)
  • 8-8.5 Months
upGradupGradData Science Bootcamp with AI
  • 6 months
Popular
upGrad KnowledgeHutupGrad KnowledgeHutData Engineer Bootcamp
  • Self-Paced
upGradupGradCertificate Course in Business Analytics & Consulting in association with PwC India
  • 06 Months
OP Jindal Global UniversityOP Jindal Global UniversityMaster of Design in User Experience Design
  • 12 Months
Popular
WoolfWoolfMaster of Science in Computer Science
  • 18 Months
New
Jindal Global UniversityJindal Global UniversityMaster of Design in User Experience
  • 12 Months
New
Rushford, GenevaRushford Business SchoolDBA Doctorate in Technology (Computer Science)
  • 36 Months
IIIT BangaloreIIIT BangaloreCloud Computing and DevOps Program (Executive)
  • 8 Months
New
upGrad KnowledgeHutupGrad KnowledgeHutAWS Solutions Architect Certification
  • 32 Hours
upGradupGradFull Stack Software Development Bootcamp
  • 6 Months
Popular
upGradupGradUI/UX Bootcamp
  • 3 Months
upGradupGradCloud Computing Bootcamp
  • 7.5 Months
Golden Gate University Golden Gate University Doctor of Business Administration in Digital Leadership
  • 36 Months
New
Jindal Global UniversityJindal Global UniversityMaster of Design in User Experience
  • 12 Months
New
Golden Gate University Golden Gate University Doctor of Business Administration (DBA)
  • 36 Months
Bestseller
Ecole Supérieure de Gestion et Commerce International ParisEcole Supérieure de Gestion et Commerce International ParisDoctorate of Business Administration (DBA)
  • 36 Months
Rushford, GenevaRushford Business SchoolDoctorate of Business Administration (DBA)
  • 36 Months
KnowledgeHut upGradKnowledgeHut upGradSAFe® 6.0 Certified ScrumMaster (SSM) Training
  • Self-Paced
KnowledgeHut upGradKnowledgeHut upGradPMP® certification
  • Self-Paced
IIM KozhikodeIIM KozhikodeProfessional Certification in HR Management and Analytics
  • 6 Months
Bestseller
Duke CEDuke CEPost Graduate Certificate in Product Management
  • 4-8 Months
Bestseller
upGrad KnowledgeHutupGrad KnowledgeHutLeading SAFe® 6.0 Certification
  • 16 Hours
Popular
upGrad KnowledgeHutupGrad KnowledgeHutCertified ScrumMaster®(CSM) Training
  • 16 Hours
Bestseller
PwCupGrad CampusCertification Program in Financial Modelling & Analysis in association with PwC India
  • 4 Months
upGrad KnowledgeHutupGrad KnowledgeHutSAFe® 6.0 POPM Certification
  • 16 Hours
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Science in Artificial Intelligence and Data Science
  • 12 Months
Bestseller
Liverpool John Moores University Liverpool John Moores University MS in Machine Learning & AI
  • 18 Months
Popular
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with concentration in Generative AI
  • 3 Years
IIIT BangaloreIIIT BangaloreExecutive Post Graduate Programme in Machine Learning & AI
  • 13 Months
Bestseller
IIITBIIITBExecutive Program in Generative AI for Leaders
  • 4 Months
upGradupGradAdvanced Certificate Program in GenerativeAI
  • 4 Months
New
IIIT BangaloreIIIT BangalorePost Graduate Certificate in Machine Learning & Deep Learning (Executive)
  • 8 Months
Bestseller
Jindal Global UniversityJindal Global UniversityMaster of Design in User Experience
  • 12 Months
New
Liverpool Business SchoolLiverpool Business SchoolMBA with Marketing Concentration
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA with Marketing Concentration
  • 15 Months
Popular
MICAMICAAdvanced Certificate in Digital Marketing and Communication
  • 6 Months
Bestseller
MICAMICAAdvanced Certificate in Brand Communication Management
  • 5 Months
Popular
upGradupGradDigital Marketing Accelerator Program
  • 05 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Corporate & Financial Law
  • 12 Months
Bestseller
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in AI and Emerging Technologies (Blended Learning Program)
  • 12 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Intellectual Property & Technology Law
  • 12 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Dispute Resolution
  • 12 Months
upGradupGradContract Law Certificate Program
  • Self paced
New
ESGCI, ParisESGCI, ParisDoctorate of Business Administration (DBA) from ESGCI, Paris
  • 36 Months
Golden Gate University Golden Gate University Doctor of Business Administration From Golden Gate University, San Francisco
  • 36 Months
Rushford Business SchoolRushford Business SchoolDoctor of Business Administration from Rushford Business School, Switzerland)
  • 36 Months
Edgewood CollegeEdgewood CollegeDoctorate of Business Administration from Edgewood College
  • 24 Months
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with Concentration in Generative AI
  • 36 Months
Golden Gate University Golden Gate University DBA in Digital Leadership from Golden Gate University, San Francisco
  • 36 Months
Liverpool Business SchoolLiverpool Business SchoolMBA by Liverpool Business School
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA (Master of Business Administration)
  • 15 Months
Popular
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Business Administration (MBA)
  • 12 Months
New
Deakin Business School and Institute of Management Technology, GhaziabadDeakin Business School and IMT, GhaziabadMBA (Master of Business Administration)
  • 12 Months
Liverpool John Moores UniversityLiverpool John Moores UniversityMS in Data Science
  • 18 Months
Bestseller
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Science in Artificial Intelligence and Data Science
  • 12 Months
Bestseller
IIIT BangaloreIIIT BangalorePost Graduate Programme in Data Science (Executive)
  • 12 Months
Bestseller
O.P.Jindal Global UniversityO.P.Jindal Global UniversityO.P.Jindal Global University
  • 12 Months
WoolfWoolfMaster of Science in Computer Science
  • 18 Months
New
Liverpool John Moores University Liverpool John Moores University MS in Machine Learning & AI
  • 18 Months
Popular
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with concentration in Generative AI
  • 3 Years
Rushford, GenevaRushford Business SchoolDoctorate of Business Administration (AI/ML)
  • 36 Months
Ecole Supérieure de Gestion et Commerce International ParisEcole Supérieure de Gestion et Commerce International ParisDBA Specialisation in AI & ML
  • 36 Months
Golden Gate University Golden Gate University Doctor of Business Administration (DBA)
  • 36 Months
Bestseller
Ecole Supérieure de Gestion et Commerce International ParisEcole Supérieure de Gestion et Commerce International ParisDoctorate of Business Administration (DBA)
  • 36 Months
Rushford, GenevaRushford Business SchoolDoctorate of Business Administration (DBA)
  • 36 Months
Liverpool Business SchoolLiverpool Business SchoolMBA with Marketing Concentration
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA with Marketing Concentration
  • 15 Months
Popular
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Corporate & Financial Law
  • 12 Months
Bestseller
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Intellectual Property & Technology Law
  • 12 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Dispute Resolution
  • 12 Months
IIITBIIITBExecutive Program in Generative AI for Leaders
  • 4 Months
New
IIIT BangaloreIIIT BangaloreExecutive Post Graduate Programme in Machine Learning & AI
  • 13 Months
Bestseller
upGradupGradData Science Bootcamp with AI
  • 6 Months
New
upGradupGradAdvanced Certificate Program in GenerativeAI
  • 4 Months
New
KnowledgeHut upGradKnowledgeHut upGradSAFe® 6.0 Certified ScrumMaster (SSM) Training
  • Self-Paced
upGrad KnowledgeHutupGrad KnowledgeHutCertified ScrumMaster®(CSM) Training
  • 16 Hours
upGrad KnowledgeHutupGrad KnowledgeHutLeading SAFe® 6.0 Certification
  • 16 Hours
KnowledgeHut upGradKnowledgeHut upGradPMP® certification
  • Self-Paced
upGrad KnowledgeHutupGrad KnowledgeHutAWS Solutions Architect Certification
  • 32 Hours
upGrad KnowledgeHutupGrad KnowledgeHutAzure Administrator Certification (AZ-104)
  • 24 Hours
KnowledgeHut upGradKnowledgeHut upGradAWS Cloud Practioner Essentials Certification
  • 1 Week
KnowledgeHut upGradKnowledgeHut upGradAzure Data Engineering Training (DP-203)
  • 1 Week
MICAMICAAdvanced Certificate in Digital Marketing and Communication
  • 6 Months
Bestseller
MICAMICAAdvanced Certificate in Brand Communication Management
  • 5 Months
Popular
IIM KozhikodeIIM KozhikodeProfessional Certification in HR Management and Analytics
  • 6 Months
Bestseller
Duke CEDuke CEPost Graduate Certificate in Product Management
  • 4-8 Months
Bestseller
Loyola Institute of Business Administration (LIBA)Loyola Institute of Business Administration (LIBA)Executive PG Programme in Human Resource Management
  • 11 Months
Popular
Goa Institute of ManagementGoa Institute of ManagementExecutive PG Program in Healthcare Management
  • 11 Months
IMT GhaziabadIMT GhaziabadAdvanced General Management Program
  • 11 Months
Golden Gate UniversityGolden Gate UniversityProfessional Certificate in Global Business Management
  • 6-8 Months
upGradupGradContract Law Certificate Program
  • Self paced
New
IU, GermanyIU, GermanyMaster of Business Administration (90 ECTS)
  • 18 Months
Bestseller
IU, GermanyIU, GermanyMaster in International Management (120 ECTS)
  • 24 Months
Popular
IU, GermanyIU, GermanyB.Sc. Computer Science (180 ECTS)
  • 36 Months
Clark UniversityClark UniversityMaster of Business Administration
  • 23 Months
New
Golden Gate UniversityGolden Gate UniversityMaster of Business Administration
  • 20 Months
Clark University, USClark University, USMS in Project Management
  • 20 Months
New
Edgewood CollegeEdgewood CollegeMaster of Business Administration
  • 23 Months
The American Business SchoolThe American Business SchoolMBA with specialization
  • 23 Months
New
Aivancity ParisAivancity ParisMSc Artificial Intelligence Engineering
  • 24 Months
Aivancity ParisAivancity ParisMSc Data Engineering
  • 24 Months
The American Business SchoolThe American Business SchoolMBA with specialization
  • 23 Months
New
Aivancity ParisAivancity ParisMSc Artificial Intelligence Engineering
  • 24 Months
Aivancity ParisAivancity ParisMSc Data Engineering
  • 24 Months
upGradupGradData Science Bootcamp with AI
  • 6 Months
Popular
upGrad KnowledgeHutupGrad KnowledgeHutData Engineer Bootcamp
  • Self-Paced
upGradupGradFull Stack Software Development Bootcamp
  • 6 Months
Bestseller
KnowledgeHut upGradKnowledgeHut upGradBackend Development Bootcamp
  • Self-Paced
upGradupGradUI/UX Bootcamp
  • 3 Months
upGradupGradCloud Computing Bootcamp
  • 7.5 Months
PwCupGrad CampusCertification Program in Financial Modelling & Analysis in association with PwC India
  • 5 Months
upGrad KnowledgeHutupGrad KnowledgeHutSAFe® 6.0 POPM Certification
  • 16 Hours
upGradupGradDigital Marketing Accelerator Program
  • 05 Months
upGradupGradAdvanced Certificate Program in GenerativeAI
  • 4 Months
New
upGradupGradData Science Bootcamp with AI
  • 6 Months
Popular
upGradupGradFull Stack Software Development Bootcamp
  • 6 Months
Bestseller
upGradupGradUI/UX Bootcamp
  • 3 Months
PwCupGrad CampusCertification Program in Financial Modelling & Analysis in association with PwC India
  • 4 Months
upGradupGradCertificate Course in Business Analytics & Consulting in association with PwC India
  • 06 Months
upGradupGradDigital Marketing Accelerator Program
  • 05 Months

40 Best IoT Project Ideas & Topics For Beginners 2024 [Latest]

Updated on 12 November, 2024

780.99K+ views
40 min read

In this article, you will learn the 40Exciting IoT Project Ideas & Topics. Take a glimpse at the project ideas listed below.

Best Simple IoT Project Ideas & Topics

Here is the complete list of smart systems, formatted with numbers:

1. Smart Agriculture System
2. Weather Reporting System
3. Home Automation System
4. Face Recognition Bot
5. Smart Garage Door
6. Smart Alarm Clock
7. Air Pollution Monitoring System
8. Smart Parking System
9. Smart Traffic Management System
10. Smart Cradle System
11. Smart Gas Leakage Detector Bot
12. Streetlight Monitoring System
13. Smart Anti-Theft System
14. Liquid Level Monitoring System
15. Night Patrol Robot
16. Health Monitoring System
17. Smart Irrigation System
18. Flood Detection System
19. Mining Worker Safety Helmet
20. Smart Energy Grid
21. Contactless Doorbell
22. Virtual Doctor Robot
23. Smart Waste Management System
24. Forest Fire Alarm System
25. Smart Baggage Tracker
26. Lavatory Vacant/Occupied System
27. Smart Pet Tracker
28. Plant Watering System
29. Home Energy Monitoring and Management
30. Health and Fitness Monitoring Device
31. Smart Pet Feeder
32. Water Quality Monitoring System
33. Safety Monitoring System for Manual Wheelchairs
34. Gesture-Controlled Contactless Switch for Smart Home
35. Automatic Emotion Journal
36. Cryptocurrency Alert System
37. Night Patrol Robot
38. Smart Banking System
39. Prison Break Monitoring and Alerting System
40. Customised Gaming Controller

Read the full article to know more in detail.

IoT Project Ideas

We live in an exciting age of technological and digital revolution. In just a decade, we’ve witnessed a radical change in the world around us. Thanks to the recent advancements in Data Science, today, we have at our disposal things like AI-powered smart assistants, autonomous cars, surgical bots, intelligent cancer detection systems, and of course, the Internet of Things (IoT). So, if you are a beginner, the best thing you can do is work on some real-time IoT project ideas.

The world currently has around 15.14 billion IoT devices. And due to advancements in technologies like 5G, this number is projected to nearly double to 29.42 billion IoT devices by 2030. This indicates the IoT ecosystem is continuously expanding and evolving.

We, here at upGrad, believe in a practical approach as theoretical knowledge alone won’t be of help in a real-time work environment. In this article, we will be exploring some interesting IoT project ideas which beginners can work on to put their knowledge to test. In this article, you will find top IoT project ideas for beginners to get hands-on experience.

You can also check out our free courses offered by upGrad under machine learning and IT technology.

Why Build IoT-Based Projects?

But first, let’s address the more pertinent question that must be lurking in your mind: why build IoT projects?

When it comes to careers in software development, it is a must for aspiring developers to work on their own projects. Developing real-world projects is the best way to hone your skills and materialize your theoretical knowledge into practical experience. The more you experiment with different IoT projects, the more knowledge you gain.

The Internet of Things is a major sensation of the 21st century. After all, who would have thought that someday we’d have access to a technology that would allow us to connect everyday objects – like thermostats, kitchen appliances, door lock systems, baby monitors, and electrical appliances – over a centralized and integrated network and control them from anywhere in the world!

Learn Advanced Certification in Cyber Security from IIITB

Essentially, IoT describes a connected network comprising multiple physical objects that have sensors and smart software embedded in them to facilitate the exchange of data among them via the Internet. However, IoT isn’t just limited to everyday household objects – you can even connect sophisticated industrial objects and systems over an IoT network. As of now, there are over 7 billion IoT devices, and this number is expected to grow to 22 billion by 2025!

An IoT network leverages a combination of mobile, cloud, and Big Data technologies along with data analytics and low-cost computing to enable the collection and exchange of data among physical objects connected within the network. And what’s impressive is that all of this is accomplished with minimal human intervention. 

As you start working on IoT project ideas, you will not only be able to test your strengths and weaknesses, but you will also gain exposure that can be immensely helpful to boost your career. Working on IoT simulation projects and IoT projects for engineering students is a fantastic way to improve efficiency and productivity. In this tutorial, you will find interesting IoT project ideas for beginners to get hands-on experience.

As the IoT technology continues to gain momentum in the modern industry, researchers and tech enthusiasts are readily investing in the development of pioneering IoT projects. In this post, we’ll talk about some of the best IoT project ideas.

Get Machine Learning Certification from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career.

What are the benefits of IoT Projects Ideas for Final Year Students?

The Internet of Things (IoT) has emerged as a transformative force, connecting physical devices and everyday objects to the digital world. IoT projects encompass various applications across various sectors, from healthcare and agriculture to manufacturing and transportation. These IoT project ideas bring many benefits, revolutionizing industries and unprecedentedly enhancing lives.

1. Improved Efficiency and Productivity

One of the primary advantages of IoT projects is the ability to streamline processes and optimize resource usage. Businesses can monitor and manage operations in real time by deploying IoT-enabled sensors and devices. This leads to enhanced efficiency, reduced downtime, and improved overall productivity. For instance, in manufacturing, IoT sensors can track production lines, identifying bottlenecks and potential failures, allowing for timely maintenance and minimal disruptions.

2. Enhanced Data Collection and Analysis

IoT projects generate vast amounts of data from connected devices and sensors. This data offers valuable insights into operations, customer behavior, and equipment performance. Businesses can make informed decisions, identify trends, and predict outcomes through data analysis, leading to better planning and resource allocation.

3. Cost Savings and Resource Management

Optimizing resource usage not only improves efficiency but also leads to cost savings. IoT projects help organizations monitor energy consumption, water usage, and other resources, allowing for better control and conservation. Smart grids, for instance, can adjust energy distribution based on real-time demand, reducing waste and cutting costs for both providers and consumers.

4. Remote Monitoring and Control

IoT projects enable remote monitoring and control of devices and systems, offering convenience and safety. For example, IoT-enabled medical devices can transmit patient data to healthcare providers, enabling remote monitoring and timely intervention. Similarly, farmers can remotely monitor crops and irrigation systems in agriculture, optimizing agricultural practices and minimizing manual labor.

5. Enhanced Customer Experience

IoT applications can potentially revolutionize the customer experience by providing personalized and connected services. Smart homes with IoT devices offer seamless automation and control, enhancing comfort and convenience for residents. Retailers can leverage IoT data to offer personalized recommendations and targeted marketing, increasing customer satisfaction and loyalty.

Looking to challenge yourself or expand your portfolio? Check out our curated list of computer science project ideas to inspire your next groundbreaking project.

6. Predictive Maintenance

One of the most significant advantages of IoT projects is predictive maintenance. By continuously monitoring the condition of equipment and machinery, businesses can predict when maintenance is needed before a breakdown occurs. This approach reduces downtime, extends the lifespan of assets, and minimizes maintenance costs.

7. Safety and Security

IoT projects ideas can significantly improve safety in various environments. In industrial settings, IoT sensors can monitor workplace conditions, detect potential hazards, and ensure safety regulations compliance. Smart cities can use IoT to monitor traffic and public spaces, enhancing security and emergency response capabilities.

8. Sustainable and Eco-Friendly Solutions

IoT projects contribute to sustainability efforts by promoting smart and eco-friendly practices. Smart buildings can optimize energy consumption based on occupancy levels, reducing carbon footprints. IoT-enabled waste management systems can also improve recycling efforts and reduce waste generation.

9. Innovation and Competitiveness

Organizations that embrace IoT projects ideas gain a competitive edge by offering innovative solutions and services. IoT-driven insights and data analytics open new opportunities for businesses to differentiate themselves in the market and adapt to evolving customer needs.

10. Transforming Industries and Creating Smart Cities

They are instrumental in transforming industries and creating smart cities. IoT enables remote patient monitoring and telemedicine in healthcare, revolutionizing healthcare delivery. IoT-based precision farming techniques enhance crop yields while minimizing resource usage in agriculture. For transportation, IoT applications improve logistics and public transportation efficiency, reducing congestion and carbon emissions in smart cities.

So, here are a few IoT Project ideas that beginners can work on:

Top 24 Best IoT Projects Ideas For Final Year College Students & Beginners

This list of IoT project ideas for students is suited for beginners and those just starting out with IoT in general. These IoT project ideas will get you going with all the practicalities you need to succeed in your career. With a goal to keep up with advancing technologies, IoT projects for engineering students serve to be the blueprint to explore technological possibilities, a chance to produce, improve, and recreate technology capable of working on minimal human intervention. 

IoT research topics can help aspirants work on their practical skills and extend their subject knowledge further through consistent practice on IoT projects for engineering students. Further, this list should get you going if you’re looking for IoT project ideas for the final year. So, without further ado, let’s jump straight into some IoT project ideas that will strengthen your base and allow you to climb up the ladder.

1. Smart Agriculture System

One of the best ideas to start experimenting you hands-on IoT projects for students is working on a smart agriculture system. As the name suggests, this IoT-based project focuses on developing a smart agricultural system that can perform and even monitor a host of farming tasks. For instance, you can schedule the system to irrigate a piece of land automatically, or you can spray fertilizers/pesticides on the crops wirelessly through your smartphone.

Not just that, this IoT-based project can also successfully monitor soil moisture through a moisture sensing system, which can work to detect dry soil. Such an advanced system can handle routine agricultural tasks, thereby allowing farmers and cultivators to focus on more manual-intensive agricultural tasks. Learners can implement a similar IoT simulation project or IoT research topics to monitor house gardens or indoor plants that often go untended.

Benefits of smart agriculture system-

  • Real-time update
  • Increased productivity
  • Remote management
  • Timely monitoring
  • Data-centric
  • Lowered operation costs
  • Time effective
  • Accurate
  • Easy to use

Factors of smart agriculture-

  • Smart contracts
  • Supply Chain
  • Analytics
  • Soil factors
  • Climate
  • Sensors
  • Research
  • Storage

Source code – Github

Also, Check out online degree programs at upGrad.

2. Weather Reporting System

This is one of the excellent IoT project ideas for beginners. This IoT-based weather reporting system is specifically designed to facilitate the reporting of weather parameters over the Internet. This is one of the best IoT projects where the system is embedded with temperature, humidity, and rain sensors that can monitor weather conditions and provide live reports of weather statistics. 

It is an always-on, automated system that sends data via a microcontroller to the web server using a WIFI connection. This data is updated live on the online server system. So, you can directly check the weather stats online without having to rely on the reports of weather forecasting agencies. The system also allows you to set threshold values and alerts for specific instances and notifies users every time the weather parameters cross the threshold value.

A few IoT projects for final year are aiming to evolve efficient usage of devices to reduce carbon footprint, which is a need of the hour. From consistent monitoring of carbon emissions to enforcing standard equipment and energy usage to operate under restricted levels, IoT’s role is evolving. Developers are leveraging smart technologies to maintain a consistent balance between nature and technology.

Benefits of Weather Reporting System-

  • Easy access to the weather report
  • Remote access
  • Compatible with various applications such as iOS, Android, etc.
  • Allows to take preventive measures
  • Allows the users to plan their activities
  • Can be carried anywhere
  • User friendly

Usage of Weather Reporting System-

  • Mountaineering
  • Agriculture
  • Fishing
  • Flood prediction
  • Defense
  • Aviation
  • Cyclone

Source code – Github

Must ReadFree deep learning course!

3. Home Automation System

Home automation is perhaps the most talked about IoT projects. IoT-based home automation project aims to automate the functioning of household appliances and objects over the Internet. All the household objects that are connected over the IoT network can be controlled and operated through your smartphone.

This is not only convenient but also gives more power to the user to control and manage household appliances from any location in the world. 

This IoT-based project uses a touch-based home automation system. The components of this project include a WiFi connection, an AVR family microcontroller, and inbuilt touch-sensing input pins. While the microcontroller is integrated with the WiFi modem to obtain commands from the user via the Internet, an LCD screen displays the system status. When the microcontroller receives a command, it processes the instructions to operate the load accordingly and shows the system status on an LCD screen. 

However, also Blockchain IoT allows homeowners to manage their home security system remotely from their smartphone. Mentioning IoT projects can help your resume look much more interesting than others.

Benefits of Home Automation System-

  • Energy efficient
  • Safe and secure
  • Convenient
  • Time efficient
  • Remote access
  • Centralised managing point
  • Cost-effective
  • Constant monitoring 
  • Customisable according to the requirements

Usage of Home Automation System-

  • Electricity monitoring
  • Lawn management
  • The air quality of home
  • Home appliances of home
  • Smart assistants- Speech automated
  • Smart Locks
  • Smart Watches
  • Smart energy meters

Source code – Github

4. Face Recognition Bot

This IoT project involves building a smart AI bot equipped with advanced facial recognition capabilities. This is one of the best IoT Projects where the intelligent AI bot is designed to recognize the faces of different people or a single person and also their unique voice. 

The system includes facial recognition features like face detection (perceives faces and attributes the same in an image), personal identification (matches an individual in your private repository containing hundreds and thousands of people), and also emotion recognition (detects a range of facial expressions including happiness, contempt, neutrality, and fear).

This combination of advanced recognition features makes for a robust security system. The system also includes a camera that lets users preview live streams through face recognition.

Benefits of Face Recognition Bot-

  • Identification of missing individuals
  • Identification of criminals/ perpetrators
  • Protection from identity theft
  • Protection from business theft
  • Better photo organisation
  • Medical treatment

Significant aspects of facial recognition-

  • 3D mapping
  •  Biometric techniques
  • Deep learning
  • Face representation
  • Face detection
  • Face recognition

Source code – Github

5. Smart Garage Door

Yes, you can use IoT technology to control and operate your garage door! The IoT-based smart garage door eliminates the need for carrying bulky keychains. All you need is to configure and integrate your smartphone with the home IoT network, and you can effortlessly open or close your garage door with just a few clicks of a button.  

This smart garage door system incorporates laser and voice commands and smart notifications for monitoring purposes, and also IFTT integration that allows you to create custom commands for Google Assistant. The smart notification option can trigger alerts in real-time to notify as and when the garage door opens or closes, which is a nifty addition. This is one of the most straightforward IoT project ideas for you to work on.

Benefits of Smart Garage Door-

  • Secure
  • Safe
  • Remote access
  • Trackable
  • Time efficient
  • Protect deliveries
  • Schedule option 
  • Easy to install
  • User friendly
  • Can be accessed through various devices

Source code – Github

6. Smart Alarm Clock

This is one of the interesting IoT project ideas. This IoT-based alarm clock functions not only as an alarm clock to wake you up every morning, but it can convert into a fully-functional device capable of performing other tasks as well. The features of this smart alarm clock include:

  • Voice command option to execute standard commands and also to initiate a video chat.
  • A text-to-speech synthesizer
  • Automatic display brightness adjustment
  • Audio amplifier volume control 
  • Alphanumeric screen for displaying text

Apart from these features, you can also add customizable features to the smart alarm clock. Interestingly enough, the alarm clock offers three ways of waking you up – by playing local mp3 files, by playing tunes from the radio station, and by playing the latest news updates as podcasts.

Benefits of Smart Alarm Clock-

  • Helps in timeline management
  • Improves sleep quality
  • Increases productivity
  • It can be connected to various devices
  • Allows the users to integrate with the playlist

Components of Smart Alarm Clock-

  • Text-to-speech synthesiser
  • Keyboard
  • Display
  • Audio Amplifier
  • Button 
  • Speaker
  • Resistors 
  • Capacitors
  • Wires

Source code – Github

7. Air Pollution Monitoring System

One of the best ideas to start experimenting your hands-on IoT projects for students is working on an Air pollution monitoring system. Air pollution is a menace in all parts of the world, and monitoring air pollution levels is a challenge that we’re facing. While traditional air pollution monitoring systems fail to monitor air pollution levels successfully and the contaminants, IoT-based air pollution monitoring systems can both monitor the level of air pollution in cities and save the data on web servers for future use. 

This smart air pollution monitoring system promotes a cost-efficient technique for determining air quality. The system is embedded with sensors that specially monitor five components of the Environmental Protection Agency’s Air Quality Index – ozone, carbon monoxide, sulfur dioxide, nitrous oxide, and particulate matter. Plus, the system also includes a gas sensor that can alert users in case of gas leaks or the presence of flammable gases. Apart from this, there’s also a temperature and humidity sensor.

Benefits of Air Pollution Monitoring System-

  • It helps to monitor the pollutants
  • Allows the decision-makers to take preventive and corrective measures
  • Helps in improving the environment
  • Trackable
  • It helps to reduce the chances of health imbalance

Parameters to measure Air Pollution Monitoring System-

  • Wind speed
  • Rainfall
  • Radiation 
  • Temperature
  • Wind direction
  • Barometric pressure

Source code – Github

8. Smart Parking System

With cities and urban areas getting crowded by the minute, finding a parking space is nothing short of a challenge. It is not only time-consuming but also quite frustrating. Thanks to IoT, there’s a solution for solving the parking problem crisis. This IoT-based smart parking system is designed to avoid unnecessary traveling and harassment in the search for an appropriate parking area. This is an excellent IoT project for beginners.

So, if you are in a parking space, this system uses an IR sensor to monitor the entire area during the run time and provide you with an image for the same. This allows you to see any free spaces in the parking lot and drive straight to it without wasting any time looking for a parking space. Also, the system is tuned to open the car gate n only if there are empty slots available in a parking space.

  • Advanced Sensor Types: Utilizes ultrasonic, magnetic, or camera-based sensors to detect parking space availability.
  • Machine Learning Optimization: Employs machine learning algorithms to analyze and optimize parking space allocation.
  • Real-Time Data Analysis: Provides a central server that processes sensor data for real-time parking management.
  • Mobile App Integration: Offers a mobile app for drivers to access real-time updates on parking availability, location, and pricing.
  • Dynamic Pricing Models: Supports dynamic pricing based on parking demand to optimize revenue and usage.
  • Data Analytics for Urban Planning: Provides data analytics that can be used for broader urban planning and management.
  • Integration with City Traffic Systems: Integrates with city traffic systems to help reduce congestion and pollution.

Benefits of Smart Parking System-

  • Less fuel consumption
  • Time efficient
  • Cost efficient
  • Productivity
  • Optimised Parking
  • Real-time monitoring
  • Inclusive to disabled 
  • Parking guided systems
  • Online payments
  • The place to recharge electric vehicle
  • Space for special permits

Source code – Github

9. Smart Traffic Management System

As the population increases, the number of vehicles plying on the road also increases inevitably. Due to the ever-increasing number of both public and private cars in cities and metropolitan areas, traffic congestion has become an everyday problem. One of the needed and best IoT projects. To combat this problem, this IoT-based project creates a smart traffic management system that can effectively manage traffic on roads, and offer free pathways to emergency vehicles like ambulances and fire trucks. 

Emergency vehicles can connect to this smart system and find signals and pathways where the traffic flow can be controlled dynamically. It flashes a green notification light for emergency vehicles. Also, this intelligent traffic management system can identify and monitor traffic violators even at night.

Benefits of Smart Traffic Management System-

  • Real-Time Management of Traffic
  • Safety from road accidents
  • Preventive measures
  • Traffic monitoring
  • Better time management
  • Environmental impacts

Factors of Smart Traffic Management System-

  • Video Traffic Detection
  • Edge Processing Capabilities
  • Pollution Analytics
  • Predictive Planning
  • Shareable data

Source code – Github

10. Smart Cradle System

The whole concept behind creating the smart cradle is to enable parents to check up on their infants and monitor their activities from afar (remote locations). 

This is one of the interesting IoT project ideas. The IoT-based smart cradle system includes a cry-detecting mechanism and live-video surveillance along with a user interface (for mobile or web). The cradle is equipped with multiple sensors that can check and monitor the humidity and temperature of the bed. On the other hand, the surveillance camera attached to the cradle will continue to send footage of the infant to the parents.

The data generated by the sensors is stored in the cloud. Additionally, the system includes a health algorithm that feeds on the sensor data to continually check the health condition of the infant and alert the parents if it senses anything unusual in the baby’s health stats.

Benefits of Smart Cradle System-

  • Allows the parents to monitor their child.
  • Instant messages on ongoings.
  • Noise detection of the baby
  • Alerts on phone
  • Camera
  • Remote access
  • Shareable data

Features of a Smart Cradle System-

  • PIR sensor for child monitoring
  • Noise Detection
  • Camera
  • Swings on the cradle

Source code – Github

11. Smart Gas Leakage Detector Bot

Gas pipes are an indispensable component of both homes and industrial companies. Any leakage in gas pipes can lead to fire accidents and also contaminate the air with pollutants, thereby causing a disastrous effect on the air and the soil. This IoT-based project is explicitly built to combat the issue of gas leakage.

And this is the perfect idea for your next IoT project!

This tiny bot includes a gas sensor that can detect any gas leaks in a building. All you have to do is insert the bot into a pipe, and it will monitor the condition of the pipe as it moves forward. This is one of the most important and best IoT projects. In case the bot detects any gas leak in the pipeline, it will transmit the location of the leakage in the pipe via an interface GPS sensor over the IoT network. The bot uses IOTgecko to receive and display any gas leakage alert and its location over the IoT network. 

  • Multi-Gas Detection: Detects various gases like natural gas, propane, and carbon monoxide.
  • Integration with Smart Systems: Ability to integrate with smart home or industrial systems for enhanced safety protocols.
  • Automatic Safety Responses: Capable of triggering ventilation systems or shutting off gas supply lines automatically to mitigate risks.
  • Smartphone Notifications: Sends prompt notifications to smartphones or central monitoring systems when gas concentrations exceed safe levels.
  • Remote Monitoring and Control: Includes a Wi-Fi module for remote monitoring and control via smartphones.
  • Automatic Gas Valve Control: Features a motorized valve that can automatically turn off the gas valve to prevent further leakage.
  • Ease of Installation: Highlights the ease of installing the system for effective use.

Benefits of Smart Gas Leakage Detector Bot-

  • Early detection of toxic gases
  • Avoid unwanted leakages
  • Prevention from unwanted leakages

Features of Smart Gas Leakage Detector Bot-

  • LCD Display
  • IoT setup
  • Gas Sensor
  • Buzzer
  • Monitoring

Source code – Github

12. Streetlight Monitoring System

Streetlights are a significant source of energy consumption. Often, streetlights continue to remain on even when there’s no one in the street. With the help of this IoT-based streetlight monitoring system, we can efficiently monitor and optimize the energy consumption of streetlights.

In this IoT-based project, street lights are fitted with LDR sensors that can monitor the movement of humans or vehicles in the street. If the sensor can catch any movement in the street, it signals the microcontroller, which then turns on the street light. Similarly, if there’s movement in the street, the microcontroller switches the lights off. This way, a substantial amount of energy can be saved. This is one of the best IoT projects for safety. 

Not just that, the smart light system also allows users to monitor the estimated power consumption based on the current intensity of a streetlight. It is incorporated with a load-sensing functionality that can detect any fault in the lights. If the system detects an error, it automatically flags a particular light as faulty and sends the data over to the IoT monitoring system so that it can be fixed promptly.

Benefits of Streetlight Monitoring System-

  • Energy efficient
  • Cost-effective
  • Lower maintenance
  • Reduce carbon emissions
  • Improved infrastructure
  • Insights
  • Analysis

Features of Streetlight Monitoring System-

  • Digitally display signs
  • Detect weather conditions 
  • Monitor traffic 
  • Wifi hosting
  • Parking management
  • Alerts

Source code – Github

13. Smart Anti-Theft System

Security is one of the primary choices for homes, businesses, and corporations. Having a robust security system helps to keep unwanted intruders at bay. The IoT-based anti-theft system is the perfect solution for safeguarding homes as well as industrial enterprises. 

This IoT-based security system is programmed to monitor the entire floor of the building for tracking any kind of unusual movement. When turned on, a single movement could trigger an alarm, thereby alerting the owners of the property about unwanted visitors. It works something like this – whenever you vacate a house or a building, the Piezo sensor is turned on for tracking any movement in and around the property. This is one of the best IoT projects to practice. 

So if an intruder were to enter the property, the sensor would send the data to the microcontroller, which then converts it into a signal for the camera to snap a picture of the intruder. This picture is then automatically sent to the users on their smartphones. Mentioning IoT projects can help your resume look much more interesting than others.

Benefits of Smart Anti-Theft System-

  • Secure
  • Helps in the protection of belongings
  • Remote access
  • Integrates alert system
  • Allows the users to access it from any device
  • Alarm system

Factors of Smart Anti-Theft System-

  • Data capturing
  • Data storage
  • Data analysis
  • Shareable data
  • SMS option
  • Alert 
  • Door and Window Contacts
  • Motion Detectors
  • System Interruption Errors

Source code – Github

14. Liquid Level Monitoring System

This IoT-based project involves building a liquid-level monitoring system that can remotely monitor a particular liquid’s level and prevent it from overflowing. This project holds immense value for the industrial sector that uses large volumes of fluids in its day-to-day operations. Apart from detecting a liquid’s level, this monitoring system can also be used to track the usage of specific chemicals and to detect leaks in pipelines. 

The system is fitted with ultrasonic, conductive, and float sensors. A WiFi module helps connect the system to the Internet and facilitates data transmission. Four ultrasonic sensors help transmit the data on the liquid level and alert the user on the same. 

Benefits of Liquid Level Monitoring System-

  • Allows to access fluid level
  • Temperature monitoring
  • Updates 
  • Alarms
  • Automatic On/ OFF pumps
  • Level Control

Features of Liquid Level Monitoring System-

  • Remotely monitor liquid levels
  • Access fluid level information
  • Buzzer/ Trigger Alarms
  • Wi-Fi Modem 
  • Display levels of liquid

Source code – Github

15. Night Patrol Robot

This is one of the best IoT project ideas. It is a well-established fact that a majority of crimes occur in the dark, at night. This IoT project aims to develop a patrolling robot that can guard your home and property at night to prevent and reduce the possibilities of crimes. 

The patrol robot is equipped with a night vision camera with the help of which it can perform a 360-degree scan of a predefined path. It will scan a particular area, and if it detects human faces and movements, it will trigger an alarm to alert the user. The camera of the patrol robot can capture an intruder’s image and send the data to the user. The robot can function in a self-sufficient manner, without requiring you to hire security guards to protect your home.  

Benefits of Night Patrol Robot-

  • Secure
  • Increases safety
  • Helps in reducing the crime rates
  • Allows the government to track or trace criminals
  • Increases women’s safety
  • Strengthen surveillance efforts

Features of Night Patrol Robot-

  • Night vision
  • Motion Sensor
  • Display monitor
  • Wi-fi setup
  • Camera Capture
  • Speech recognition
  • Remote Access

Source code – Github

16. Health Monitoring System

This is one of the interesting IoT project ideas to create. This IoT-powered health monitoring system is designed to allow patients to take charge of their own health actively. The system will enable users to monitor their body vitals and send the data to qualified doctors and healthcare professionals. The doctors can then provide patients with immediate solutions and guidance based on their health condition. The sensors in the application can monitor patient vitals like blood pressure, sugar level, and heartbeat. If the vital stats are higher/lower than usual, the system will immediately alert the doctor. 

The idea behind creating this system is to allow patients and doctors to connect remotely for the exchange of medical data and expert supervision. You can use this application from any location in the world. It is an Arduino-based project – the communication occurs between the Arduino platform and an Android app via Bluetooth.

Benefits of Health Monitoring System

  • Cost-effective
  • Time effective
  • Accuracy
  • Easy access
  • Prompt diagnosis
  • Shareable
  • Health monitoring

Features of Health Monitoring System-

  • Sensor Module
  • Data Acquisition
  • Data Monitoring
  • Data Processing
  • Easy UI
  • Shareable
  • Wi-fi module

Source code – Github

17. Smart Irrigation System

Often, farmers have to irrigate the land manually. Not only is this a time-intensive task, but it is also labor-intensive. After all, it is quite challenging for farmers to continuously monitor the moisture level of the whole field and sprinkle the pieces of land that require water. This IoT project is a smart irrigation system that can analyze the moisture level of the soil and the climatic conditions and automatically water the field as and when required. 

You can use the smart irrigation system to check the moisture level, and set a predefined threshold for an optimum moisture level of soil, on reaching which the power supply will get cut off. An Arduino/328p microcontroller controls the motor that supplies water, and there’s an on/off switch with which you can start or stop the motor. The smart irrigation system will automatically stop if it starts raining.

Benefits of Smart Irrigation System-

  • Water conservation
  • Time efficient
  • Cost-effective
  • Remotely control sprinklers 
  • Increased soil quality
  • Sensors (Rain, Freeze, Wind, etc.)
  • Soil moisture sensor

Features of Smart Irrigation System-

  • Water Pump
  • Soil Moisture Sensor
  • Processing unit
  • Water Schedule Setup
  • Data Monitoring

Source code – Github

18. Flood Detection System

Floods are a common natural disaster that occurs almost every year in our country. Floods not only destroy agricultural fields and produce, but they also cause significant damage to vast stretches of area and property. This is why early flood detection is extremely vital to prevent the loss of life and valuable assets. 

This IoT-based flood detection system is built to monitor and track different natural factors (humidity, temperature, water level, etc.) to predict a flood, thereby allowing us to take the necessary measures to minimize the damage caused. This IoT project uses sensors to collect data for all the relevant natural factors. For instance, a digital temperature humidity sensor detects fluctuations in humidity and temperature. On the other hand, a float sensor continually monitors the water level. 

Besides providing a system equipped with temperature sensors and float sensors to gauge the possible flood conditions, comprehending the geographical features of the space can help create shelters and collect required amenities beforehand. At the same time, flood detection systems are capable enough to gauge the time a fresh wave of the flood could take to reach a particular location. Systems like these are significant to maintaining the well-being of communities. Advanced detection systems created through IoT projects for final year can alert residents in time, allowing for early evacuation planning.

Benefits of Flood Detection System

  • Risk Management
  • Helps in saving lives
  • Allows the stakeholders to save infrastructure
  • Cost-effective
  • Time effective
  • Real-time data
  • Flood forecasting
  • Mapping using GIS

Components of Flood Detection System-

  • Water Sensor
  • Wind Sensor
  • Data management
  • Ultrasonic sensor
  • Power Supply
  • Microcontrollers
  • Modem

Source code – Github

19. Mining Worker Safety Helmet

This is one of the interesting IoT project ideas. Mining workers work under extremely hazardous and dangerous conditions. Underground environments are full of risks, so there is always a fear of unpleasant accidents for miners. This mining worker safety helmet uses a microcontroller-based circuit to track the mining site’s environment and evaluate the safety of the workers. 

The safety helmet is equipped with an RF-based tracking system that helps transmit the data over the IoT network. An atmega microcontroller-based RF tracker circuit receives the data that is sent by the helmet nodes. Based on this data, the system maps the current location of workers in real time as they move through the mining site.

The helmet also includes a panic (emergency) button. If you press this button, an emergency sign will show up over the IoT web interface. This will alert the management to take the necessary steps for ensuring the workers’ safety.

Benefits of Mining Worker Safety Helmet-

  • Identification of the worker’s last location
  • Alarm in case of hazardous situation
  • Safety 
  • Safeguarding of lives
  • Infrastructure management
  • Time effective
  • Cost-effective

Features of Mining Worker Safety Helmet-

  • Cell place
  • Gas vent
  • Flexible button to untie
  • Sensors to send alarm 
  • Location tracker
  • Mini camera if required

Source code – Github

20. Smart Energy Grid

At present, energy grids are not optimized. Often when the electricity grid of a given region fails, the entire area suffers a blackout. This usually hinders the daily activities of people. This is one of the best IoT project ideas which proposes a solution to rectify this issue by creating a smart electricity grid.

This IoT-based smart energy grid uses an ATmega family controller to monitor and control the system’s activities. It uses WiFi technology to communicate over the Internet via the IoTGecko webpage. This smart grid’s primary task is to facilitate the transmission line’s re-connection to an active grid in case a particular grid fails.

So, if an energy grid becomes faulty, the system will switch to the transmission lines of another energy grid, thus, maintaining an uninterrupted electricity supply to the specific region whose energy grid failed. The system uses two bulbs to indicate valid and invalid users. Registered personnel can log in to the IoTGecko webpage and view updates on which grid is active and faulty. This is one of the best IoT Projects to add to your resume.

The smart energy grid can also monitor energy consumption and detect incidents of electricity theft.

Benefits of Smart Energy Grid-

  • Energy efficient
  • Resourceful
  • Time effective
  • Cost-effective
  • Improved reliability
  • Enhanced power quality
  • Reduce greenhouse gas emissions
  • Digitalisation
  • Decarbonisation

Source code – Github

21. Contactless Doorbell

All the systems around have become digitalised and automated. Covid on other hand has given a new perspective to contactless interaction.

The machine uses the raspberry pi controller. The machine also uses a camera and speaker for the process.

Benefits of Contactless  Doorbell-

  • Increased security
  • Prevention from thefts
  • Alert the owners
  • Voice assistance 
  • Alarm 
  • Wi-fi module
  • Camera capture
  • Remote access
  • Can be connected through various devices

Features of Contactless Doorbell-

  • Automatic visitor recognition
  • Power Supply
  • LAN/ Ethernet
  • Vision Sensor
  • PIR Sensor

Source code – Github

22. Virtual Doctor Robot

Doctors are highly required in the medical field. Their expertise saves lives every day, and they are seen as one of the most integral parts of our society. But with the rising cases and mishaps, especially in the case of emergencies and remote locations, it becomes difficult for doctors to be present everywhere. 

Virtual doctors play an important role to provide medical expertise even in remote locations. They could interact with the patients and provide medical advice just like a human. 

Benefits of Virtual Doctor Robot-

  • Inclusive to all types of locations
  • They could move around different locations
  • Assess medical reports over video call
  • Provide medical treatment at the earliest

Source code – Github

23. Smart Waste Management System

The cities are smarter and are keeping up with the technology. It is time to do away with the age-old practice of waste disposal and adapt to the smart waste management system.

Municipal professionals can make great use of this technology. Whenever the dustbin is about to be filled up totally, it sends an alarm or an alert to the team that they could fetch the waste in time. 

It also helps in segregating the waste into dry or wet garbage. Moreover, they could also help them to save energy and time.

Benefits of Smart Waste Management System-

  • Reduction of cost of collection
  • In time pickups
  • Stop overflowing of garbage
  • Environment friendly
  • CO2 Emission Reduction

Components of Smart Waste Management System-

  • IoT platform
  • Sensors
  • Integrated to various applications
  • Wi-fi 
  • Alarm/ Alert

Source code – Github

24. Forest Fire Alarm System

The machine helps to identify the causes of fire threats and take immediate measures to prevent those. This satellite and optical system can detect large landscapes. The alerts can be sent in time in order to take necessary actions in time. 

Benefits of Forest Fire Alarm System-

  • Safeguards environment
  • Helps to protect the environment, lives, infrastructure, and more.
  • Allows to gauge temperature, humidity, pressure, and wind
  • Geographical mapping of the location

Source code – Github

25. Smart Baggage Tracker

The Smart Baggage Tracker is one of the brilliant IoT project topics aimed at making traveling more convenient and stress-free. This project involves placing a small, lightweight device in your luggage that tracks its location in real-time. Using a smartphone app, you can quickly determine the exact whereabouts of your baggage at any time. 

Benefits of Smart Baggage Tracker-

  • Reduce the instances of lost or misplaced luggage.
  • Secured tagging in case of lost/stolen luggage. 
  • Weight monitoring 
  • Temperature control

Source code – Github

26. Lavatory Vacant/Occupied System

The Lavatory Vacant/Occupied System is a cutting-edge IoT project that offers a real-time solution for monitoring the occupancy of public and private restrooms. By using sensors and indicators, it provides instant updates on whether the restroom is available or in use. The system aims to optimize restroom management and enhance the overall user experience.

Benefits of Lavatory Vacant/Occupied System-

  • Improve privacy and user comfort.
  • Increase efficiency in cleaning and maintenance.
  • Reduce waiting times and manage queues effectively.
  • Enhance the utilization of facilities, particularly in high-traffic areas.
  • Foster sanitary conditions by preventing overcrowding.

Source code – Github

27. Smart Pet Tracker

The Smart Pet Tracker is a cutting-edge IoT-based project that aims to keep our beloved pets secure and healthy. Employing advanced tracking systems, this device can be easily attached to your pet’s collar, allowing you to monitor their whereabouts in real-time and guarantee their safety and well-being.

Benefits of the Smart Pet Tracker-

  • Know exactly where your pet is at any given time.
  • Get notified immediately if your pet leaves a pre-defined ‘safe zone’.
  • Understand your pet’s patterns and behaviors better.
  • Monitor your pet’s health and activity levels to ensure they’re staying active and healthy.
  • Adjust the tracking and alert parameters to suit your specific needs.
  • The Smart Pet Tracker is user-friendly and can be set up within minutes.
  • Affordable

Source code – Github

28. Plant Watering System

The IoT Plant Watering System is an interesting IoT-based mini project combining technology with nature to ensure plants are properly hydrated. This system uses sensors to check how moist the soil is and waters the plants automatically when the soil gets too dry. 

It’s a huge improvement for home gardeners because it reduces the chances of plants not getting enough or getting too much water.

Benefits include-

  • The system only waters plants when necessary, optimizing water usage.
  • The automated nature of the system relieves individuals from the need to manually water plants.
  • By maintaining appropriate moisture levels, the system promotes healthier and more productive plants.
  • This automation frees up time that can otherwise be used elsewhere.
  • The system can be scaled to suit everything from small household gardens to large agricultural fields.

Source code – Github

29. Home Energy Monitoring and Management

IoT has brought an exciting transformation in the Home Energy Monitoring and Management landscape. This great IoT project idea for beginners aims to provide homeowners with real-time data on their energy usage, allowing them to make informed decisions to minimize waste and reduce their energy bills.

Benefits-

  • Promotes conscious energy consumption, reducing waste, and promoting sustainability.
  • Homeowners can cut down their electricity bills by identifying and reducing unnecessary power usage.
  • The system is user-friendly, with a simple interface that doesn’t require technical expertise to operate.

Source code – Github

30. Health and Fitness Monitoring Device

The Health and Fitness Monitoring Device is an innovative solution that stands out among IoT projects. This device employs the principles of the Internet of Things (IoT) to monitor and track fitness metrics in real-time.

The benefits –

  • Allows integration of various technologies, offering students a practical understanding of IoT project ideas.
  • Facilitates real-time monitoring of health and fitness data, demonstrating the potential and utility of IoT in healthcare.

Source code – Github

31. Smart Pet Feeder

The IoT-based Smart Pet Feeder is an exciting and invaluable project idea for engineering students looking to delve into the world of IoT projects. This project is a perfect blend of technology and utility, designed to automatically feed pets at predetermined times.

The Smart Pet Feeder uses an IoT device to trigger the release of pet food from a dispenser into a feeding bowl. The owner can customize feeding schedules and portion sizes through a smartphone application, ensuring that pets follow a balanced diet even when the owner is not around.

Benefits of the Smart Pet Feeder-

  • Ensures that pets are fed at regular intervals without manual intervention.
  • Allows pet owners to customize feeding times and portion sizes based on their pets’ needs.
  • Offers owners the ability to monitor feeding schedules remotely, offering peace of mind.
  • Helps in maintaining a balanced diet for pets, contributing to their overall well-being.

Source code – Github

32. Water Quality Monitoring System

The Water Quality Monitoring System uses the IoT to monitor water quality in real-time. Such IoT-based projects are instrumental in addressing significant environmental issues, pushing them beyond the periphery of just IoT project ideas to something more impactful.

This project is incredibly important as it helps maintain the health and well-being of communities by ensuring clean and safe drinking water.

Benefits of the Water Quality Monitoring System-

  • Real-time monitoring and instant feedback on water quality.
  • Automation of the water monitoring process, reducing human error.
  • Potential for early detection of water contaminants, preventing health hazards.

Source code – Github

33. Safety Monitoring System for Manual Wheelchairs

The Safety Monitoring System for Manual Wheelchairs is a good example of IoT-based projects that offer life-improving solutions. This practical and vital IoT project idea uses a series of sensors and alarms to monitor the safety of wheelchair users.

Here are some key benefits-

  • Ensures user safety with real-time monitoring and hazard detection.
  • Increases user independence by enabling more confident navigation.
  • Provides peace of mind to caregivers with immediate alert systems.

Source code – Github

34. Gesture-Controlled Contactless Switch for Smart Home

The Gesture-Controlled Contactless Switch for Smart Homes is a cutting-edge IoT project for engineering students. This project uses gesture-recognition technology to operate switches without physical contact, contributing significantly to the development of smart homes.

Benefits of the Gesture-Controlled Contactless Switch for Smart Homes-

  • Enhance user convenience with easy and intuitive controls.
  • Improve safety by eliminating the need for physical contact with switches.
  • Facilitate energy efficiency through smart control of home appliances.

Source code – Github

35. Automatic Emotion Journal

The Automatic Emotion Journal is an excellent example that demonstrates how IoT can be integrated into our day-to-day lives, enhancing our emotional well-being.

This unique project uses IoT technology to capture an individual’s emotional state throughout the day. Using sensors and data analysis, it can record mood changes, providing a comprehensive emotional journal without the user having to manually input any information.

Benefits of the Automatic Emotion Journal-

  • Offers valuable insights into emotional patterns.
  • Encourages users to pay attention to their emotional well-being.

Source code – Github

36. Cryptocurrency Alert System

The Cryptocurrency Alert System is an innovative IoT project idea that brings together the worlds of technology and finance. This system monitors the volatile cryptocurrency market and sends real-time alerts based on specific conditions set by the user.

Benefits of the Cryptocurrency Alert System-

  • Empowers users with real-time data, enabling informed decision-making.
  • Encourages learning about both IoT and the burgeoning field of cryptocurrency.

Source code – Github

37. Night Patrol Robot

The Night Patrol Robot is an exceptional example of IoT projects that engineering students can undertake. Using advanced technology, this robotic device performs security patrols during nighttime hours, effectively providing a layer of safety and security wherever it’s deployed.

Source code – Github

38. Smart Banking System

The Smart Banking System is a prime example of IoT-based projects that students can take up to understand the practical applications of IoT. In this project, IoT technology is employed to enhance banking services like money transfer, making them more efficient and customer-friendly.

Benefits of the Smart Banking System-

  • Enhances understanding of how IoT can be employed to improve banking services continuously.

Source code – Github

39. Prison Break Monitoring And Alerting System

The Prison Break Monitoring and Alerting System is one of the innovative IoT projects that harness the power of IoT technology. This IoT project idea uses various sensors and alarms fused with IoT to monitor prison cells and alert the relevant authorities in case of any suspicious activities or breaches.

Key benefits-

  • Real-time monitoring provides comprehensive surveillance.
  • Automated alerts
  • Potentially save considerable amounts of money spent on traditional security measures.

Source code – Github

40. Customised Gaming Controller

The Customized Gaming Controller is an exciting IoT project that empowers students to design and build their own gaming gear.

Key benefits of Customised Gaming Controller-

  • Provides a hands-on approach to IoT concepts.
  • Students learn about circuitry, programming, and IoT technology, enhancing their tech-savvy skills.
  • The project encourages unique ideas and designs, fostering creativity amongst students.

Source code – Github

IoT Projects Examples

  • Smart Home Automation
  • Wearable Health Monitors
  • Smart Farming Systems
  • Industrial Internet of Things (IIoT)
  • Connected Car Applications
  • Smart Retail Systems
  • Energy Management Systems
  • Smart City Solutions
  • Environmental Monitoring
  • Smart Grid Technology

Future for IoT

With the ever-growing need for improvement and better accessibility, IoT estimates a dynamic future globally. Introduction to 5G and Metaverse are proof of the oncoming bright future for IoT’s flexible and improved variants. Assimilating the virtual world with reality through Metaverse is on its way, and IoT-based projects with source code are only a step away from joining hands to bring in digitally-driven physical devices. Cellular IoT’s growth is another aspect market expects to see in the coming years to adopt remote monitoring across diverse fields, including agriculture and smart cities. 

Extended IoT simulation projects are gaining popularity as a way to prepare young minds for the upcoming IoT trends. But perks are not the only thing accompanying IoT in the near future. 

Experts also predict heightened security threats for IoT-driven areas. A significant number of evolving IoT sectors are under the threat of botnets. In early 2021, sources reported a 35% to 51% spike in botnet attacks across individual devices and organizations through sophisticated instruments. As technological advancements improve, so do intrusion methods. Fortunately, constant improvements in security intelligence through IoT-based projects with source code are keeping such intrusions in check and aim to strengthen network and application firewalls further.

What are some college projects for IoT?

For college students exploring IoT, a variety of projects can provide practical experience and insight into this innovative field. Some potential project ideas include developing a Smart Irrigation System that uses sensors to optimize water usage in gardening, creating a Home Security System with motion detectors and remote alerts, or building an Energy Management System that monitors and controls energy consumption in real-time.

Other ideas could involve setting up an Environmental Monitoring System to track air quality or temperature changes, or implementing a Health Monitoring System that collects and analyzes data from wearable devices to track fitness and health metrics. These projects not only enhance technical skills but also encourage students to think creatively about solving real-world problems with technology.

Wrapping Up 

In this article, we have covered 24 IoT project ideas. These IoT-based projects are just a few examples of how IoT technology can be used and implemented to create innovative products. With further advancements in technology, it is highly likely that more such radical and groundbreaking IoT-based projects will enter the canvas of our everyday lives.

If you wish to improve your IoT skills, you need to get your hands on these IoT project ideasNow go ahead and put to test all the knowledge that you’ve gathered through our IoT project ideas guide to building your very own IoT Projects!

If you are interested to know more about IoT, deep learning, and artificial intelligence, check out our Executive PG Programme in Machine Learning & AI program which is designed for working professionals and provides 30+ case studies & assignments, 25+ industry mentorship sessions, 5+ practical hands-on capstone projects, more than 450 hours of rigorous training & job placement assistance with top firms.

upGrad partners with leading faculty and industry leaders to nurture dynamic young professionals and help them land lucrative jobs in the tech domain. Besides, learners get to have one-on-one sessions with professional mentors for extensive guidance and counseling.

Refer to your Network!

If you know someone, who would benefit from our specially curated programs? Kindly fill in this form to register their interest. We would assist them to upskill with the right program, and get them a highest possible pre-applied fee-waiver up to ₹70,000/-

You earn referral incentives worth up to ₹80,000 for each friend that signs up for a paid programme! Read more about our referral incentives here.

Explore our popular tutorials on various technologies, including JavaScript, SQL,DBMS, Data Structure, JQuery, HTML, Cyber Security, C++, Deep Learning, and Agile Scrum.


 

Frequently Asked Questions (FAQs)

1. How easy it is to implement these projects?

These projects are very basic, someone with a good knowledge of IoT can easily manage to pick and finish any of these projects.

2. Can I do this projects on Internship?

Yes, as mentioned, these project ideas are basically for Students or Beginners. There is a high possibility that you get to work on any of these project ideas during your internship.

3. Why do we need to build IoT projects?

When it comes to careers in software development, it is a must for aspiring developers to work on their own projects. Developing real-world projects is the best way to hone your skills and materialize your theoretical knowledge into practical experience.

4. How is IoT useful in real life?

IoT is an integral part of our daily lives now; we all use IoT either knowingly or unknowingly. The best example of IoT in our day-to-day lives is home automation applications. Smart lights and smart blinds are becoming increasingly common today in modern smart homes. Then, our smartwatches that can track our heartbeat, count steps, etc., are also another brilliant application of IoT. Most of our smartphones come with biometric locks nowadays. These are again applications of IoT in real life. The barcode scanners we find in shopping malls are also IoT applications connected to computers and billing machines, which are all a part of the IoT network.

5. Do IoT engineers have to write code?

IoT devices or the hardware that we see are built up of several components, of which the IoT software needs to be programmed using computer languages. So IoT engineers have to write code using programming languages for IoT software to function. Several programming languages go into creating successful IoT applications, each with its own unique features and benefits. Some of the most commonly employed programming languages used are Python, Java, C++, MySQL, and C, among others. These programming languages are used to write the instructions contained in IoT software, which is embedded in the IoT hardware.

6. What skills and aptitude do you need to become an IoT developer?

If you aspire to become an IoT developer, then first and foremost, you need to have some basic familiarity with programming languages that are needed for IoT software development. Knowing Python and JavaScript can be an added advantage. Having an understanding of the role of data is vital in IoT. Trying your hands-on practice IoT projects is a brilliant way to gain confidence. Along with technical skills, soft skills are also indispensable in becoming a successful IoT developer.



SUGGESTED BLOGS

Technology will surely kill some jobs, but not all of them

898.89K+

Technology will surely kill some jobs, but not all of them

“Remember that dystopian view of the future in which technology displaces millions of people from their jobs? It’s happening” Jeff Weiner, CEO LinkedIn, wrote when Microsoft announced it was acquiring LinkedIn. Some of the top companies in the world such as handset maker Foxconn, US-based retail company Walmart and McDonald’s are now turning to robots and automation. It’s true that some jobs may become defunct as this shift becomes more pronounced. At the same time, these technologies doubtless offer lots of opportunities for many other types of jobs such as digital curation and preservation, data mining and big data analytics. Top Machine Learning and AI Courses Online Master of Science in Machine Learning & AI from LJMU Executive Post Graduate Programme in Machine Learning & AI from IIITB Advanced Certificate Programme in Machine Learning & NLP from IIITB Advanced Certificate Programme in Machine Learning & Deep Learning from IIITB Executive Post Graduate Program in Data Science & Machine Learning from University of Maryland To Explore all our certification courses on AI & ML, kindly visit our page below. Machine Learning Certification The shift of skills in jobs Most industries in India and around the world are undergoing a digital transformation, and skills to utilise emerging technologies like mobility, cloud computing, business intelligence, artificial intelligence, machine learning, robotics and nanotechnology among others are gaining popularity. In fact, the World Economic Forum estimates that (pdf) 65% of children entering school today will ultimately end up working in jobs that don’t yet exist. For example, demand for data analysts — a relatively new occupation — increased by almost 90% by the end of 2014 within a year. Many big e-commerce players, credit firms, airlines, hospitality, BFSI and retail industries already use analytics in a major way. In India, the analytics and business intelligence industry together is sized around 10 billion and is expected to grow by 22% to 26.9 billion by 2017. Skill deprivation: Education alone won’t guarantee a job! Human cognition will be in demand in the automation age When we speak of manual work being supplanted by technology, we must keep in mind that routine jobs are most susceptible to being replaced by automation. And while non-cognitive and routine work is decreasing, knowledge-oriented work is increasing. The demand for labour adept at managing such technology is on the rise – a trend that is likely to intensify as our processes become more technologically complex and disruptive. Humans are discovering newer ways of enhancing their productivity and efficiency. Most of the pattern-driven work is slowly getting automated as technology presents new ways to speed it up. But this doesn’t mean humans will be useless. They will be the ones who will need to identify problems and ask the right questions. Trending Machine Learning Skills AI Courses Tableau Certification Natural Language Processing Deep Learning AI Enrol for the Machine Learning Course from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. Demand for newer jobs will remain History shows us that jobs have consistently been rendered obsolete with the advent of technology and machines. When the washing machine was invented, those who professionally hand-washed clothes faced large-scale unemployment and redundancy. People had to learn a more complex skill in a similar area or enter a new profession altogether. Similarly, drivers may be out of jobs if driverless cars become a norm in the future but other jobs that require manufacturing, programming and sale of such cars will have high demand. This is the way old jobs metamorphose into new ones and the economy learns to keep up. There’ll Be A Billion-Plus Job-Seekers By 2050! India ripe for tech driven roles The world is set for a technology boom with information technology jobs expected to grow by 22% through 2020 — and India is one of the leaders of the troupe. To capitalise, young job-seekers have to train themselves and take charge of technology-driven roles such as product managers, application developers, data analysts and digital marketers among others. And the rising number of startups in India, especially in the online space, provides a fertile ground. In fact, software startups in India are going to create 80,000 jobs by the following year itself. So jobs that seem to be at risk, may be like molecules – splitting further and creating more jobs – just of a different kind. Instead of worrying about unemployment, those entering the workforce need to keep one finger on the pulse of evolving technology, and invest in training themselves to acquire new skill sets. Popular AI and ML Blogs & Free Courses IoT: History, Present & Future Machine Learning Tutorial: Learn ML What is Algorithm? Simple & Easy Robotics Engineer Salary in India : All Roles A Day in the Life of a Machine Learning Engineer: What do they do? What is IoT (Internet of Things) Permutation vs Combination: Difference between Permutation and Combination Top 7 Trends in Artificial Intelligence & Machine Learning Machine Learning with R: Everything You Need to Know AI & ML Free Courses Introduction to NLP Fundamentals of Deep Learning of Neural Networks Linear Regression: Step by Step Guide Artificial Intelligence in the Real World Introduction to Tableau Case Study using Python, SQL and Tableau
Read More

by Mayank Kumar

07 Jul'16
Keep an Eye Out for the Next Big Thing: Machine Learning

5.2K+

Keep an Eye Out for the Next Big Thing: Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are buzzwords that are increasingly being used to discuss upcoming trends in Data Science and other technologies. However, are these two concepts really peas in the same pod? Artificial Intelligence is a broader concept of smart machines carrying out various tasks on their own. While Machine Learning is an application of Artificial Intelligence where machines learn from data provided to them using various types of algorithms. Therefore, Machine Learning is a method of data analysis that automates analytical model building, allowing computers to find hidden insights without being explicitly programmed to do so. Sounds like the pitch-perfect solution to all our technological woes, doesn’t it? Top Machine Learning and AI Courses Online Master of Science in Machine Learning & AI from LJMU Executive Post Graduate Programme in Machine Learning & AI from IIITB Advanced Certificate Programme in Machine Learning & NLP from IIITB Advanced Certificate Programme in Machine Learning & Deep Learning from IIITB Executive Post Graduate Program in Data Science & Machine Learning from University of Maryland To Explore all our certification courses on AI & ML, kindly visit our page below. Machine Learning Certification Evolution of Machine Learning Arthur Samuel, an American pioneer in the field of computer gaming and artificial intelligence, coined the term ‘Machine Learning’ in 1959 while at IBM. During its early days, Machine Learning was born from pattern recognition with the theory that computers can learn from patterns in data without being programmed to perform specific tasks. Researchers interested in Artificial Intelligence later developed algorithms with which computers or machines could learn from data. As a result of this, whenever the machines were exposed to new data, they were able to independently adapt as well Trending Machine Learning Skills AI Courses Tableau Certification Natural Language Processing Deep Learning AI Enrol for the Machine Learning Course from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. It’s a science that’s not new, but one that’s gaining fresh momentum, thanks mainly to new computing technologies that have evolved over the last few decades. Many Machine Learning algorithms have been around for a long time. But, the ability to automatically apply complex mathematical calculations to large data sets is a fresh development being witnessed. Here are a few examples of Machine Learning applications you might be familiar with: Online recommendations from Amazon and Netflix. YouTube detecting and removing terror content on the platform. Knowing what customers are saying about you on Twitter The Rise of Machine Learning The emergence of the internet, as well as the massive increase in digital information being generated, stored, and made available for analysis, are seen to be the two important factors that have led to the emergence of Machine Learning. With the magnitude of quality data from the internet, economical data storage options and improved data processing capabilities, Machine Learning algorithms are seen as a vehicle propelling the development of Artificial Intelligence at a scorching pace in recent times. Neural Networks A neural network works on a system of probability by being able to make statements, decisions, or predictions based on data fed to it. Moreover, a feedback loop enables further “learning” by sensing; it also modifies the learning process based on whether its decisions are right or wrong. An artificial neural network is a computer system with node networks inspired from the neurons in the animal brain. Such networks can be taught to recognise and classify patterns through witnessing examples rather than telling the algorithm how exactly to recognise and classify patterns. Machine Learning derived applications of neural networks can read pieces of text and recognise the nature of the text – whether it is a complaint or congratulatory note. They can also listen to a piece of music, decide whether it is likely to make someone happy or sad, and find other pieces of similar music. What’s more, they can even compose music expressing the same mood or theme. In the near future, with the help of Machine Learning and Artificial Intelligence, it should be possible for a person to communicate and interact with electronic devices and digital information thanks to another emerging field of AI called Natural Language Processing (NLP). NLP has become a source of cutting-edge innovation in the past few years, and one which is heavily reliant on Machine Learning. NLP applications attempt to understand human communication, both written as well as spoken, and communicate using various languages. In this context, Machine Learning helps machines understand the nuances in human language and respond in a way that a particular audience is likely to comprehend. So, who is actually using it? Most industries working with large amounts of data have recognised the value of Machine Learning. Large companies glean vital real-time actionable insights from stored data and are hence able to increase efficiency or gain an advantage over their competitors. Financial services Banks and other businesses use Machine Learning to identify important insights in data generated and thereby prevent frauds. These insights can identify investment opportunities or help investors know when to trade. Data mining can also identify clients with high-risk profiles or use cyber surveillance to warn customers about fraud and thereby minimise identity theft. Marketing and sales E-commerce websites use Machine Learning technology to analyse buying history based on previous purchases, to recommend items that you may like and promote other items. The retail industry is enlisting the ability of websites to capture data, analyse it, and use it to personalise a shopping experience or implement marketing campaigns. Summing up, Artificial Intelligence and, in particular, Machine Learning, certainly has a lot to offer today. With its promise of automating mundane tasks as well as offering creative insights, industries in every sector from banking to healthcare and manufacturing are reaping the benefits. Popular AI and ML Blogs & Free Courses IoT: History, Present & Future Machine Learning Tutorial: Learn ML What is Algorithm? Simple & Easy Robotics Engineer Salary in India : All Roles A Day in the Life of a Machine Learning Engineer: What do they do? What is IoT (Internet of Things) Permutation vs Combination: Difference between Permutation and Combination Top 7 Trends in Artificial Intelligence & Machine Learning Machine Learning with R: Everything You Need to Know AI & ML Free Courses Introduction to NLP Fundamentals of Deep Learning of Neural Networks Linear Regression: Step by Step Guide Artificial Intelligence in the Real World Introduction to Tableau Case Study using Python, SQL and Tableau Eventually, scientists hope to develop human-like Artificial Intelligence that is capable of increasing the speed of various automated functions, especially with the advent of chatbots in the internet realm. Much of the exciting progress that we have seen in recent years is due to progressive changes in Artificial Intelligence, which have been brought about by Machine Learning. This is clearly why Machine Learning is poised to become the next big thing in the data sciences sphere. So go ahead, UpGrad yourself to stay ahead of the curve.
Read More

by Varun Dattaraj

17 Oct'17
The Difference between Data Science, Machine Learning and Big Data!

7.87K+

The Difference between Data Science, Machine Learning and Big Data!

Many professionals and ‘Data’ enthusiasts often ask, “What’s the difference between Data Science, Machine Learning and Big Data?” This is a question frequently asked nowadays. Here’s what differentiates Data Science, Machine Learning and Big Data from each other: Data Science Data Science follows an interdisciplinary approach. It lies at the intersection of Maths, Statistics, Artificial Intelligence, Software Engineering and Design Thinking. Data Science deals with data collection, cleaning, analysis, visualisation, model creation, model validation, prediction, designing experiments, hypothesis testing and much more. The aim of all these steps is just to derive insights from data. Top Machine Learning and AI Courses Online Master of Science in Machine Learning & AI from LJMU Executive Post Graduate Programme in Machine Learning & AI from IIITB Advanced Certificate Programme in Machine Learning & NLP from IIITB Advanced Certificate Programme in Machine Learning & Deep Learning from IIITB Executive Post Graduate Program in Data Science & Machine Learning from University of Maryland To Explore all our certification courses on AI & ML, kindly visit our page below. Machine Learning Certification Digitisation is progressing at an exponential rate. Internet accessibility is improving at breakneck speed. More and more people are getting absorbed into the digital ecosystem. All these activities are generating a humongous amount of data. Companies are currently sitting on a data landmine. But data, by itself, is not of much use. This is where Data Science comes into the picture. It helps in mining this data and deriving insights from it; for taking meaningful action. Various Data Science tools can help us in the process of insight generation. If you are a beginner and interested to learn more about data science, check out our data scientist courses from top universities. Frameworks exist to help derive insights from data. A framework is nothing but a supportive structure. It’s a lifecycle used to structure the development of Data Science projects. A lifecycle outlines the steps —  from start to finish — that projects usually follow. In other words, it breaks down the complex challenges into simple steps. This ensures that any significant phase, which leads to the generation of actionable insights from data, is not missed out. One such framework is the ‘Cross Industry Standard Process for Data Mining’, abbreviated as the CRISP-DM framework. The other is the ‘Team Data Science Process’ (TDSP) from Microsoft. Let’s understand this with the help of an example. A bank named ‘X’, which has been in business for the past ten years. It receives a loan application from one of its customers. Now, it wants to predict whether this customer will default in repaying the loan. How can the bank go about achieving this task? Like every other bank, X must have captured data regarding various aspects of their customers, such as demographic data, customer-related data, etc. In the past ten years, many customers would have succeeded in repaying the loan, but some customers would have defaulted. How can this bank leverage this data to improve its profitability? To put it simply, how can it avoid providing loans to a customer who is very likely to default? How can they ensure not losing out on good customers who are more likely to repay their debts? Data Science can help us resolve this challenge. Raw Data —> Data Science —-> Actionable Insights Let’s understand how various branches of Data Science will help the bank overcome its challenge. Statistics will assist in the designing of experiments, finding a correlation between variables, hypothesis testing, exploratory data analysis, etc. In this case, the loan purpose or educational qualifications of the customer could influence their loan default. After performing data cleaning and exploratory study, the data becomes ready for modeling. Statistics and artificial intelligence provide algorithms for model creation. Model creation is where machine learning comes into the picture. Machine learning is a branch of artificial intelligence that is utilised by data science to achieve its objectives. Before proceeding with the banking example, let’s understand what machine learning is. Trending Machine Learning Skills AI Courses Tableau Certification Natural Language Processing Deep Learning AI Enrol for the Machine Learning Course from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. Machine Learning “Machine learning is a form of artificial intelligence. It gives machines the ability to learn, without being explicitly programmed.” How can machines learn without being explicitly programmed, you might ask? Aren’t computers just devices made to follow instructions? Not anymore. Machine learning consists of a suite of intelligent algorithms, enabling machines to learn without being explicitly programmed for it. Machine learning helps you learn the objective function — which maps the inputs to the target variable, or independent variables to the dependent variables. In our banking example, the objective function determines the various demographics, customer and behavioural variables which influences the probability of a loan default. Independent attributes or inputs are the demographic, customer and behavioural variables of a customer. The dependent variable is either ‘to default’ or not. The objective function is an equation which maps these inputs to outputs. It’s a function which tells us which independent variables influence the dependent variable, i.e. the tendency to default. This process of deriving an objective function, which maps inputs to outputs is known as modelling. Initially, this objective function will not be able to predict precisely whether a customer will default or not. As the model encounters new instances, it learns and evolves. It improves as more and more examples become available. Ultimately, this model reaches a stage where it will be able to tell with a certain degree of precision. hings like, which customer is going to default, and whom the bank can rely on to improve its profitability. Machine learning aims to achieve ‘generalisability’. This means, the objective function — which maps the inputs to the output — should apply to the data, which hasn’t encountered it, yet. In the banking example, our model learns patterns from the data provided to it. The model determines which variables will influence the tendency to default. If a new customer applies for a loan, at this point, his/her variables are not yet seen by this model. The model should be relevant to this customer as well. It should predict reliably whether this customer will default or not. If this model is unable to do this, then it will not able to generalise the unseen data. It is an iterative process. We need to create many models to see which work, and which don’t. Data science and analysis utilise machine learning for this kind of model creation and validation. It is important to note that all the algorithms for this model creation do not come from machine learning. They can enter from various other fields. The model needs to be kept relevant at all times. If the conditions change, then the model — which we created earlier — may become irrelevant. The model needs to be checked for its predictability at different times and needs to be modified if its predictability reduces. For the banking employee to take an instant decision the moment a customer applies for a loan, the model needs to be integrated with the bank’s IT systems. The bank’s servers should host the model. As a customer applies for a loan, his variables must be captured from a website and utilised by the model running on the server. Then, this model should convey the decision — whether the credit can be granted or not — to the bank employee, instantly. This process comes under the domain of information technology, which is also utilised by data science. In the end, it is all about communicating the results from the analysis. Here, the presentation and storytelling skills are required to demonstrate the effects from the study efficiently. Design-thinking helps in visualising the results, and effectively tell the story from the analysis. Big Data The final piece of our puzzle is ‘Big Data’. How is it different from data science and machine learning? According to IBM, we create 2.5 Quintillion (2.5 × 1018) bytes of data every day! The amount of data which companies gather is so vast that it creates a large set of challenges regarding data acquisition, storage, analysis and visualisation. The problem is not entirely regarding the quantity of data that is available, but also its variety, veracity and velocity. All these challenges necessitated a new set of methods and techniques to deal with the same. Big data involves the four ‘V’s — Volume, Variety, Veracity, and Velocity — which differentiates it from conventional data. Volume: The amount of data involved here is so humongous, that it requires specialised infrastructure to acquire, store and analyse it. Distributed and parallel computing methods are employed to handle this volume of data. Variety: Data comes in various formats; structured or unstructured, etc. Structured means neatly arranged rows and columns. Unstructured means that it comes in the form of paragraphs, videos and images, etc. This kind of data also consists of a lot of information. Unstructured data requires different database systems than traditional RDBMS. Cassandra is one such database to manage unstructured data. Veracity:  The presence of huge volumes of data will not lead to actionable insights. It needs to be correct for it to be meaningful. Extreme care needs to be taken to make sure that the data captured is accurate, and that the sanctity is maintained, as it increases in volume and variety. Popular AI and ML Blogs & Free Courses IoT: History, Present & Future Machine Learning Tutorial: Learn ML What is Algorithm? Simple & Easy Robotics Engineer Salary in India : All Roles A Day in the Life of a Machine Learning Engineer: What do they do? What is IoT (Internet of Things) Permutation vs Combination: Difference between Permutation and Combination Top 7 Trends in Artificial Intelligence & Machine Learning Machine Learning with R: Everything You Need to Know AI & ML Free Courses Introduction to NLP Fundamentals of Deep Learning of Neural Networks Linear Regression: Step by Step Guide Artificial Intelligence in the Real World Introduction to Tableau Case Study using Python, SQL and Tableau Velocity: It refers to the speed at which the data is generated. 90% of data in today’s world was created in the last two years alone. However, this velocity of information generated is bringing its own set of challenges. For some businesses, real-time analysis is crucial. Any delay will reduce the value of the data and its analysis for business. Spark is one such platform which helps analyse streaming data. As time progresses, new ‘V’s get added to the definition of big data. But — volume, variety, veracity, and velocity — are the four essential constituents which differentiate data from big data. The algorithms which deal with big data, including machine learning algorithms, are optimised to leverage a different hardware infrastructure, that is utilised to handle big data. To summarise, Executive PG Programme in Data Science is an interdisciplinary field with an aim to derive actionable insights from data. Machine learning is a branch of artificial intelligence which is utilised by data science to teach the machines the ability to learn, without being explicitly programmed. Volume, variety, veracity, and velocity are the four important constituents which differentiate big data from conventional data.
Read More
Natural Language Generation: Top Things You Need to Know

6.14K+

Natural Language Generation: Top Things You Need to Know

From a linguistic point of view, language was created for the survival of human beings. The effective communication helped a primitive man to hunt, gather and survive in groups. This means a language is necessary to carry out all activities needed for not only survival but also a meaningful existence of human beings. As humans evolved so did their literary skills. From pictorial scripts to well developed universal ones, we have made an impressive progress. In fact, such remarkable progress that a machine developed by humans now can read data, write text and not in a machine, binary language but a real, conversational language. Natural Language Generation has made this possible. Top Machine Learning and AI Courses Online Master of Science in Machine Learning & AI from LJMU Executive Post Graduate Programme in Machine Learning & AI from IIITB Advanced Certificate Programme in Machine Learning & NLP from IIITB Advanced Certificate Programme in Machine Learning & Deep Learning from IIITB Executive Post Graduate Program in Data Science & Machine Learning from University of Maryland To Explore all our certification courses on AI & ML, kindly visit our page below. Machine Learning Certification What is Natural Language Generation? Natural language is an offshoot of Artificial Intelligence. It is a tool to automatically analyse data, interpret it, identify the important information and narrow it down to a simple text, to make decision making in business easier, faster and of course, cheaper. It crunches numbers and drafts a narrative for you. Trending Machine Learning Skills AI Courses Tableau Certification Natural Language Processing Deep Learning AI Learn ML courses from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. What are the different variations of Natural Language Generation? Basic Natural Language Generation: The basic form of NLG converts data into text through Excel-like functions. For example, a mail merge that restates numbers into a language. Templated Natural Language Generation: In this type of NGL tool, a user takes the call on designing content templates and interpreting the output. Templated systems are restricted in their capability to scan multiple data sources, perform advanced analytics. Advanced Natural Language Generation: It is the ‘smartest’ way of analysing data. It processes the data right from the beginning and separates it based on its significance for a particular audience, and then writes the narrative with relevant information in a conversational tone. For example, if a data analyst wants to know how a particular product is doing in a market, an advanced NLG tool would write a report by segregating the data of only the required product. Do we really need natural language generation? A number of devices are connected to the internet creating a huge Internet of Things. All these devices are creating data at a lightning speed leading to Big Data generation. It is almost humanly impossible to analyse, interpret and draw rational interference from this enormous data. Along with data analysis and accurate interpretation the need for the optimum use of resources, cost cutting and time management are the essentials for a modern business to survive, grow and flourish. Natural Language Generation helps up to effectively achieve all these goals in one go. Additionally, when a machine can do these routine tasks, and accurately. So, valuable human resources can indulge themselves in the activities that require innovation, creativity and problem-solving. Will Natural Language Generation kill jobs? First of all, not all kinds of narratives can be written by Natural Language Generation tools. It is only for creating a text based on data. Creative writing, engaging content is developed not only by analytical skills but with the help of major emotional involvement. The passion of an individual, their skills, their ability to cater complex terms in simpler formats can’t be replaced. Additionally, to rationalise the text created by Natural Language Generation tools, human intervention is critical. Natural Language Generation only augments the job and enriches the life of employees by freeing them from menial jobs. Alain Kaeser, founder of Yseop has rightly acknowledged that- “The next industrial revolution will be the artificial intelligence revolution and the automation of knowledge work and repetitive tasks to enhance human capacity”. Why should you get a hang of Natural Language Generation? A research commissioned by Forrester Research anticipated a 300% increase in investment in artificial intelligence in 2017 compared to 2016. The Artificial Intelligence market will grow from $8 billion in 2016 to more than $47 billion in 2020. Based on this report, Forbes magazine has come up with a list of the ‘hottest ten Artificial Intelligence technologies’ that will rule the market in the near future. Natural Language Generation is one of them and it is set to see a huge boost. Examples and Applications of Natural Language Generation Natural Language Generation techniques are put to use across various industries as per their requirements. Healthcare-Pharma, Banking services, Digital marketing… it’s everywhere! From fund reporting in finance and campaign analytics reporting in marketing to personalised client alerts for preparing dashboards in sales and customer service maintenance, it is used to generate effective results for all departments in an organisation. Let’s have a quick look at how NLG has varied applications in various departments: Marketing – Two main responsibilities of a marketing department are designing market strategy and conducting market research. Both of these activities heavily depend on data analysis, and in today’s world of big data, it is becoming increasingly complex. Natural Language Generation tools can help you scan big data, analyse it and write reports for you within a few hours. Sales – A sales analysis report indicates the trends in a company’s sales volume over a period of time. A sales analysis report throws light on the factors that affects sales, like season, competitors strategy, advertising efforts etc. Managers use sales analysis reports to recognise market opportunities and areas where they could increase volume. These reports are purely based on humongous data. Natural Language Generation programs save your time and efforts of manually scanning data, finding trends and writing reports. Once you feed the inputs, it takes care of all of these activities. Banking and finance – May it be a finance department of an organisation or an investment bank, financial reports stating the financial health of a company needs to be written and sent out to shareholders, investors, rating agencies, government agencies etc. The general financial statements like balance sheets, Statement of cash flows, Income statement etc. are loaded with numbers and a reader likes to have a quick understanding of these statements. Natural Language Generation software scans through these statements and presents this information in a simple, text format rather than complicated accounting one. Healthcare and medicine – Recently Natural Language Generation tools are being used to summarise e-medical records. Additional research in this area is opening doors to prudent medical decision-making for medical professionals. It is also being used in communicating with patients, as a part of patient awareness programs in India, as per the NCBI report. The data collected through medical research like what kind of lifestyle diseases are most dreadful or what kinds of habits are healthy can be summarized in a simple language for patients which is extremely useful for the doctors to make a case for their advice. And this is just the tip of the iceberg. The applications of NLG tools are widespread already and are ready to take off to greater heights in the future.   Techniques of natural language generation – How to get started A refined Natural Language Generation system needs to inject some aspects of planning and amalgamation of information to enable the NLG tools to generate the text which appears natural and interesting. The general stages of natural language generation, as proposed by Dale and Reiter in their book ‘Building Natural Language Generation Systems’ are: Content determination: In this stage, a data analyst must decide what kind of information to present by using their discretion with respect to relevance. For example, deciding what kind of information a share trader would want to know vs what kind of information a dealer in the commodity market would want to know. Document structuring: In this stage, a user will have to decide the sequence, format of content and the desired template. For example, to decide the order of large cap, mid cap, small cap shares while writing a narrative about equity movement in the stock market. Aggregation: No repetition is the basic rule of any report writing. To keep it simple and improve readability, merging sentences, omitting repetitive words, phrases etc, falls under this stage. For example, if NLG software is writing a report on sales and there is no substantial change in volume of sales for a few months, there are chances NLG software might write repetitive paragraphs for no substantial information. You will then have to condense it in a way it does not become long and boring. Lingual choice: Deciding what words to use exactly to describe particular concepts. For example, deciding whether to use the word ‘medium’ or ‘moderate’ while describing a change. Best software products available for natural language generation There are a variety of software products available to help you get started with Natural Language Generation. Quill, Syntheses, Arria, Amazon Polly, Yseop are popular ones. You can make a decision based on the industry you are operating in, for the department you will be deploying the tool, exact nature of report creation, etc. Let us see what kind of aid does these programs offer to the businesses. Yseop: Yseop Compose’s Natural Language Generation software enables data-driven decision making by explaining insights in a plain language. Yseop Compose is the only multilingual Natural Language Generation software and hence truly global. Amazon Polly: It is a software that turns text into lifelike speech, allowing you to create applications that talk, and build entirely new categories of speech-enabled products. Arria: Arria NLG Platform is the one that integrates cutting-edge techniques in data analytics, artificial intelligence and computational linguistics. It analyses large and diverse data sets and automatically writes tailored, actionable reports on what’s happening within that data, with no human intervention, at vast scale and speed. Quill: It is an advanced NLG platform which comprehends user intent and performs relevant data analysis to deliver Intelligent Narratives—automated stories full of audience-relevant, insightful information. Synthesys: It is one of the popular NLG software products that scans through all data and highlights the important people, places, organizations, events and facts being discussed, resolve highlighted points and determines what’s important, connecting the dots together and figures out what the final picture means by comparing it with the opportunities, risks and anomalies users are looking for. Natural Language Generation tools automate analysis and increase the efficacy of Business Intelligence tools. Rather than generating charts and tables, NLG tools interpret the data and draft analysis in a written form that communicates precisely what’s important to know. These tools perform regular analysis of predefined data sets, eliminate the manual efforts required to draft reports and the skilled labour required to analyse and interpret the results. Popular AI and ML Blogs & Free Courses IoT: History, Present & Future Machine Learning Tutorial: Learn ML What is Algorithm? Simple & Easy Robotics Engineer Salary in India : All Roles A Day in the Life of a Machine Learning Engineer: What do they do? What is IoT (Internet of Things) Permutation vs Combination: Difference between Permutation and Combination Top 7 Trends in Artificial Intelligence & Machine Learning Machine Learning with R: Everything You Need to Know AI & ML Free Courses Introduction to NLP Fundamentals of Deep Learning of Neural Networks Linear Regression: Step by Step Guide Artificial Intelligence in the Real World Introduction to Tableau Case Study using Python, SQL and Tableau What are the best resources to learn Natural Language Generation? Gartner, a leading research and advisory company forecasts that most companies will have to employ a Chief Data officer by 2019. With the gigantic amount of data available, it is important to decide which information can add business value, drive efficiency and improve risk management. This will be the responsibility of Data Officers. With increasing global demand for the profession, there can be no better time to learn about Natural Language Generation which is a critical part of Data Science and Artificial Intelligence. Though Natural Language generation has a huge scope, there are very few comprehensive academic programs designed to train candidates to be future ready. However, with a great vision, UpGrad offers a PG Diploma in Machine Learning and AI, in partnership with IIIT-Bangalore, which aims to build highly skilled professionals in India to cater to the increasing global demand. It gives you a chance to learn from a comprehensive collection of case-studies, hand-picked by industry experts, to give you an in-depth understanding of how Machine Learning & Artificial Intelligence impact industries like Telecom, Automobile, Finance & more. What are you waiting for? Don’t let go of this wonderful opportunity, start exploring today!
Read More

by Maithili Pradhan

30 Jan'18
A Beginner’s Guide To Natural Language Understanding

8.3K+

A Beginner’s Guide To Natural Language Understanding

“A computer would deserve to be called intelligent if it could deceive a human into believing that it was human.” – Alan Turing Best Machine Learning and AI Courses Online Master of Science in Machine Learning & AI from LJMU Executive Post Graduate Programme in Machine Learning & AI from IIITB Advanced Certificate Programme in Machine Learning & NLP from IIITB Advanced Certificate Programme in Machine Learning & Deep Learning from IIITB Executive Post Graduate Program in Data Science & Machine Learning from University of Maryland To Explore all our courses, visit our page below. Machine Learning Courses The entire gamut of artificial intelligence is based on machines being able to ‘understand’ and ‘respond’ to human beings. Which is impossible without the capability of machines to interact with humans in their natural language, like other human beings. Moreover, understanding does not involve the mere exchange of information and data but an exchange of emotions, feelings, ideas and intent. Can machines ever do that? Well, the answer is affirmative and it is not even that surprising anymore. What is this miraculous technology that smoothly facilitates the interaction between humans and machines? It is Natural Language Understanding. What is Natural Language Understanding? Natural Language Understanding is a part of Natural Language Processing. It undertakes the analysis of content, text-based metadata and generates summarized content in natural, human language. It is opposite to the process of Natural Language Generation. NLG deals with input in the form of data and generates output in the form of plain text while Natural Language Understanding tools process text or voice that is in natural language and generates appropriate responses by summarizing, editing or creating vocal responses. In-demand Machine Learning Skills Artificial Intelligence Courses Tableau Courses NLP Courses Deep Learning Courses Get Machine Learning Certification from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. Natural Language Understanding Vs Natural Language Processing Natural Language Processing is a wide term which includes both Natural Language Understanding and Natural Language Generations along with many other techniques revolving around translating and analysing natural language by machines to perform certain commands.    Examples of Natural Language Processing Natural Language Processing is everywhere and we use it in our daily lives without even realising it. Do you know how spam messages are separated from your emails? Or autocorrect and predictive typing that saves so much of our time, how does that happen? Well, it is all part of Natural Language Processing. Here are some examples of Natural Language Processing technologies used widely: Intelligent personal assistants – We are all familiar with Siri and Cortana. These mobile software products that perform tasks, offer services, with a combination of user input, location awareness, and the ability to access information from a variety of online sources are undoubtedly one of the biggest achievements of natural language processing. Machine translation – To read a description of a beautiful picture on Instagram or to read updates on Facebook, we all have used that ‘see translation’ command at least once. And google translation services helps in urgent situations or sometimes just to learn few new words. These are all examples of machine translations, where machines provide us with translations from one natural language to another. Speech recognition – Converting spoken words into data is an example of natural language processing. It is used for multiple purposes like dictating to Microsoft Word, voice biometrics, voice user interface, etc. Affective computing – It is nothing but emotional intelligence training for machines. They learn to understand your emotions, feelings, ideas to interact with you in more humane ways. Natural language generation – Natural language generation tools scan structured data, undertake analysis and generate information in text format produced in natural language. Natural language understanding – As explained above, it scans content written in natural languages and generates small, comprehensible summaries of text. Learn ML courses from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career. Best tools for Natural Language Understanding available today Natural Language Processing deals with human language in its most natural form and on a real-time basis, as it appears in social media content, emails, web pages, tweets, product descriptions, newspaper articles, and scientific research papers, etc, in a variety of languages. Businesses need to keep a tab on all this content, constantly. Here are a few popular natural language understanding software products which effectively aid them in this daunting task. Wolfram – Wolfram Alpha is an answer engine developed by Wolfram Alpha LLC (a subsidiary of Wolfram Research). It is an online service that provides answers to factual questions by computing the answer from externally sourced, “curated data”. Natural language toolkit – The Natural Language Toolkit, also known as NLTK, is a suite of programs used for symbolic and statistical natural language processing (NLP) for the English language. It is written in the Python programming language and was developed by Steven Bird and Edward Loper at the University of Pennsylvania. Stanford coreNLP – Stanford CoreNLP is an annotation-based NLP pipeline that offers core natural language analysis. The basic distribution provides model files for the analysis of English, but the engine is compatible with models for other languages. GATE (General Architecture for Text Engineering) – It offers a wide range of natural language processing tasks. It is a mature software used across industries for more than 15 years. Apache openNLP – The Apache OpenNLP is a toolkit based on machine learning to process natural language text. It is written in Java and is produced by Apache software foundation. It offers services like tokenizers, chucking, parsing, part of speech tagging, sentence segmentation, etc. Applications of Natural Language Understanding As we have already seen, natural language understanding is basically nothing but a smart machine reading comprehension. Now let’s have a close look at how it is used to promote the efficiency and accuracy, while saving time and efforts, of human resources, which can then be put to better use. Collecting data and data analysis – To be able to serve well, a business must know what is expected out of them. Data on customer feedback is not numeric data like sales or financial statements. It is open-ended and text heavy. For companies to identify patterns and trends throughout, this data and taking action as per identified gaps or insights, is crucial for survival and growth. More and more companies are realizing that implementing a natural language understanding solution provides strong benefits to analysing metadata like customer feedback and product reviews. Natural language understanding in such cases proves to be more effective and accurate than traditional methods like hand-coding. It helps the customer’s voice to reach you clearer and faster, which leads to effective strategizing and productive implementation. Reputation monitoring –  Customer feedback is just a tip of the iceberg as compared to the real feelings of customers about the brand. As customers, we hardly participate in customer survey feedbacks. Most of the real customer sentiments hence are trapped in unstructured data. News, blog posts, chats, and social media updates contain huge amounts of such data which is more natural and can be used to know the ‘real’ feelings of customers about the product or service. Natural language understanding software products help businesses to scan through such scattered data and draw practical inferences. Customer service – Natural Language Understanding is able to communicate with untrained individuals and can understand their intent. NLU is capable of understanding the meaning in spite of some human errors like mispronunciations or transposed letters or words. It also uses algorithms that break down human speech to structured ontology and fishes out the meaning, intent, sentiment, and the crux of human speech. One of the most important goals of NLU is to create chatbots or human interacting bots that can effectively communicate with humans without any human supervision. There are various software products like Nuance which are already involved in customer interaction. Popular AI and ML Blogs & Free Courses IoT: History, Present & Future Machine Learning Tutorial: Learn ML What is Algorithm? Simple & Easy Robotics Engineer Salary in India : All Roles A Day in the Life of a Machine Learning Engineer: What do they do? What is IoT (Internet of Things) Permutation vs Combination: Difference between Permutation and Combination Top 7 Trends in Artificial Intelligence & Machine Learning Machine Learning with R: Everything You Need to Know AI & ML Free Courses Introduction to NLP Fundamentals of Deep Learning of Neural Networks Linear Regression: Step by Step Guide Artificial Intelligence in the Real World Introduction to Tableau Case Study using Python, SQL and Tableau Automated trading – Capital market trading automation is not a new phenomenon anymore. Multiple software products and platforms are now available that analyse market movements, the profile of industries and financial strength of a company and based on technical analysis design the trading patterns. Advanced Natural Language Understanding tools which scan through various sources like financial statements, reports, market news are the basis of automated trading systems. Market Intelligence – “What are competitors doing?” is one of the most critical information businesses need on a real-time basis. Information influences markets. Information exchange between various stakeholders designs and redesigns market dynamics all the time. Keeping a close watch on the status of an industry is essential to developing a powerful strategy, but the channels of content distribution today (RSS feeds, social media, emails) generate so much information that it’s been increasingly difficult to keep a tab on such unstructured, multi-sourced content. Financial markets have started using natural language understanding tools rigorously to keep track of information exchange in the market and help them reach it immediately. Due to such varied functions carried out by natural language understanding programs, its importance in trade, business, commerce and the industry is ever increasing. It is a smart move to learn natural language understanding programs to ensure yourself a successful career. What is the best way to learn Natural Language Understanding? The best way to prepare yourself for a brighter future in technological endeavors is to understand the algorithms of Artificial intelligence. The Post Graduate Diploma in Machine Learning and AI by UpGrad offers a chance to master concepts like Neural Networks, Natural Language Processing, Graphical Models and Reinforcement Learning. The most unique aspect of this course is the career support. And, the industry mentorship, which will help you prepare yourself for intense competition in the industry, within your actual job. So, let’s learn to use software products widely used in industry mentioned earlier like NLKT. This program aims at producing well-rounded data scientists and AI professionals with thorough knowledge of mathematics, expertise in relevant tools/languages and understanding of cutting-edge algorithms and applications. Start preparing today for a better tomorrow! Learn ML courses from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career.
Read More

by Maithili Pradhan

30 Jan'18
Neural Networks for Dummies: A Comprehensive Guide

10.99K+

Neural Networks for Dummies: A Comprehensive Guide

Our brain is an incredible pattern-recognizing machine. It processes ‘inputs’ from the outside world, categorizes them (that’s a dog; that’s a slice of pizza; ooh, that’s a bus coming towards me!), and then generates an ‘output’ (petting the dog; the yummy taste of that pizza; getting out of the way of the bus!). Best Machine Learning and AI Courses Online Master of Science in Machine Learning & AI from LJMU Executive Post Graduate Programme in Machine Learning & AI from IIITB Advanced Certificate Programme in Machine Learning & NLP from IIITB Advanced Certificate Programme in Machine Learning & Deep Learning from IIITB Executive Post Graduate Program in Data Science & Machine Learning from University of Maryland To Explore all our courses, visit our page below. Machine Learning Courses All of this with little conscious effort, almost impulsively. It’s the very same system that senses if someone is mad at us, or involuntarily notices the stop signal as we speed past it. Psychologists call this mode of thinking ‘System 1’, and it includes innate skills — like perception and fear — that we share with other animals. (There’s also a ‘System 2’, to know more about it, check out the extremely informative Thinking, Fast and Slow by Daniel Kahneman). How is all of this related to Neural Networks, you ask? Wait, we’ll get there in a second. Look at the image above, just your regular numbers, distorted to help you explain the learning of Neural Networks better. Even looking cursorily, your mind will prompt you with the words “192”. You surely didn’t go “Ah, that seems like a straight line, I think it’s a 1”. You didn’t compute it – it happened instantly. In-demand Machine Learning Skills Artificial Intelligence Courses Tableau Courses NLP Courses Deep Learning Courses Fascinating, right? There is a very simple reason for this – you’ve come across the digit so many times in your life, that by trial and error, your brain automatically recognizes the digit if you present it with something even remotely close to it. Let’s cut to the chase. What exactly is a Neural Network? How does it work? By definition, a neural network is a system of hardware or softwares, patterned after the working of neurons in the human brain. Basically, it helps computers think and learn like humans. An example will make this clearer: As a child, if we ever touched a hot coffee mug and it burnt us, we made sure not to touch a hot mug ever again. But did we have any such concept of hurt in our conscience BEFORE we touched it? Not really. This adjustment of our knowledge and understanding of the world around us is based on recognizing patterns. And, like us, computers, too, learn through the same type of pattern recognition. This learning forms the whole basis of the working of neural networks. Traditional computer programs work on logic trees – If A happens, then B happens. All the potential outcomes for each of the systems can be preprogrammed. However, this eliminates the scope of flexibility. There’s no learning there. And that’s where Neural Networks come into the picture! A neural network is built without any specific logic. Essentially, it is a system that is trained to look for and adapt to, patterns within data. It is modeled exactly after how our own brain works. Each neuron (idea) is connected via synapses. Each synapse has a value that represents the probability or likelihood of the connection between two neurons to occur. Take a look at the image below: What exactly are neurons, you ask? Simply put, a neuron is just a singular concept. A mug, the colour white, tea -, the burning sensation of touching a hot mug, basically anything. All of these are possible neurons. All of them can be connected, and the strength of their connection is decided by the value of their synapse. Higher the value, better the connection. Let’s see one basic neural network connection to make you understand better: Each neuron is the node and the lines connecting them are synapses. Synapse value represents the likelihood that one neuron will be found alongside the other. So, it’s pretty clear that the diagram shown in the above image is describing a mug containing coffee, which is white in colour and is extremely hot. All mugs do not have the properties like the one in question. We can connect many other neurons to the mug. Tea, for example, is likely more common than coffee. The likelihood of two neurons being connected is determined by the strength of the synapse connecting them. Greater the number of hot mugs, the stronger the synapse. However, in a world where mugs are not used to hold hot beverages, the number of hot mugs would decrease drastically. Incidentally, this decrease would also result in lowering the strength of the synapses connecting mugs to heat. So, Becomes This small and seemingly unimportant description of a mug represents the core construction of neural networks. We touch a mug kept on a table — we find that it’s hot. It makes us think all mugs are hot. Then, we touch another mug – this time, the one kept on the shelf – it’s not hot at all. We conclude that mugs in the shelf aren’t hot. As we grow, we evolve. Our brain has been taking in data all this time. This data makes it determine an accurate probability as to whether or not the mug we’re about to touch will be hot. Neural Networks learn in the exact same way. Now, let’s talk a bit aboutthe first and the most basic model of a neural network: The Perceptron! What is a Perceptron? A perceptron is the most basic model of a neural network. It takes multiple binary inputs: x1, x2, …, and produces a single binary output. Let’s understand the above neural network better with the help of an analogy. Say you walk to work. Your decision of going to work is based on two factors majorly: the weather, and whether it is a weekday or not. The weather factor is still manageable, but working on weekends is a big no! Since we have to work with binary inputs, let’s propose the conditions as yes or no questions. Is the weather fine? 1 for yes, 0 for no. Is it a weekday? 1 yes, 0 no. Remember, we cannot explicitly tell the neural network these conditions; it’ll have to learn them for itself. How will it decide the priority of these factors while making a decision? By using something known as “weights”. Weights are just a numerical representation of the preferences. A higher weight will make the neural network consider that input at a higher priority than the others. This is represented by the w1, w2…in the flowchart above. “Okay, this is all pretty fascinating, but where do Neural Networks find work in a practical scenario?” Real-life applications of Neural Networks If you haven’t yet figured it out, then here it is, a neural network can do pretty much everything as long as you’re able to get enough data and an efficient machine to get the right parameters. Anything that even remotely requires machine learning turns to neural networks for help. Deep learning is another domain that makes extensive use of neural networks. It is one of the many machine learning algorithms that enables a computer to perform a plethora of tasks such as classification, clustering, or prediction. With the help of neural networks, we can find the solution of such problems for which a traditional-algorithmic method is expensive or does not exist. Neural networks can learn by example, hence, we do not need to program it to a  large extent. Neural networks are accurate and significantly faster than conventional speeds. Because of the reasons mentioned above and more, Deep Learning, by making use of Neural Networks, finds extensive use in the following areas: Speech recognition: Take the example of Amazon Echo Dot – magic speakers that allow you to order food, get news and weather updates, or simply buy something online just by talking it out. Handwriting recognition: Neural networks can be trained to understand the patterns in somebody’s handwriting. Have a look at Google’s Handwriting Input application – which makes use of handwriting recognition to seamlessly convert your scribbles into meaningful texts. Face recognition: From improving the security on your phone (Face ID) to the super-cool Snapchat filters – face recognition is everywhere. If you’ve ever uploaded a photo on Facebook and were asked to tag the people in your photo, you know what face recognition is! Providing artificial intelligence in games: If you’ve ever played chess against a computer, you already know how artificial intelligence powers games and game development. It’s to the extent that players use AI to improve upon their tactics and try their strategies first-hand. Popular AI and ML Blogs & Free Courses IoT: History, Present & Future Machine Learning Tutorial: Learn ML What is Algorithm? Simple & Easy Robotics Engineer Salary in India : All Roles A Day in the Life of a Machine Learning Engineer: What do they do? What is IoT (Internet of Things) Permutation vs Combination: Difference between Permutation and Combination Top 7 Trends in Artificial Intelligence & Machine Learning Machine Learning with R: Everything You Need to Know AI & ML Free Courses Introduction to NLP Fundamentals of Deep Learning of Neural Networks Linear Regression: Step by Step Guide Artificial Intelligence in the Real World Introduction to Tableau Case Study using Python, SQL and Tableau In Conclusion… Neural networks form the backbone of almost every big technology or invention you see today. It’s only fair to say that imagining deep/machine learning without neural networks is next to impossible. Depending on the way you implement a network and the kind of learning you put to use, you can achieve a lot out of a neural network, as compared to a traditional computer system. Learn ML courses from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career.
Read More

by Reetesh Chandra

06 Feb'18