Internet of Things (IoT)

IoT will affect most industries and business sectors – around 30% of tasks and up to 60% of occupations
could be automated, and almost every occupation has the potential of partial automation (Source: McKinsey Global Institute)

$6 trillion will be spent on IoT solutions over the next 5 years. (Source: Business Insider)

Average annual salary for an IoT Architect is $179,000 (Source: Indeed)

4.2 million IoT developer jobs created by 2020 (Source: VisionMobile)

To remain competitive and successful in the digital economy, professionals should have an understanding of what IoT is and how it can be used to create business solutions. Learn major components of the Internet of Things and examine ways of integrating sensors, communication and multimedia technologies and use cloud services to make optimised business decisions.

Roles across Industries

The Internet of Things (IoT) is expanding at a rapid rate, and it is becoming increasingly important for professionals to understand what it is, how it works, and how to harness its power to improve business.

  • IoT Product Manager
  • IoT Architect
  • IoT Developer
  • Robotics programmer
  • Industrial Networking engineer
  • Industrial Data scientist
  • IoT integration developer
  • LTE stack developer

Module 1: IoT Introduction and reference architecture

Course 1: IoT introduction

Examine the concept of IoT and understand what constitutes an IoT design solution. Realise many real life IoT use cases. Get full understanding of ‘things’ that make up IoT, how they communicate with Internet.

Key topics: IoT, ‘things’ in IoT, Hardware in IoT, Energy Harvesting in devices, Networking & programming in IoT, MQTT, CoAP, 6LoWPAN,Gateways, IP, DNS, Big Data, Security in IoT, Network.

Course 2: Introduction of Data science and Analytics in IoT

Learn about major components of IoT and examine ways of analysing data acquired form sensors and make intelligent business decision based on the analysis through various software techniques.

Key topics: Natural Language processing, Multimedia processing, Speech and data science, Speech production and perception, speech features, visual matching and recognition techniques, vision Intelligence.

Module 2: IoT and Embedded system programming

Course 1: The Arduino Platform and C programming

This course will cover programming the Arduino using C code and accessing various interfaces.

Key topics: Arduino Environment & IDE, programmes, Debugging, UART, SPI, I2C.

Course 2: Interfacing with the Arduino

Learn how to use different types of sensors with Arduino and how to interact with outside world through sensors and actuators.

Key topics: Sensors & Actuators examples and demo, I2C communication & Libraries, Arduino Shield
and integration, Ethernet & Wi-Fi shields.

Course 3: The Raspberry Pi & Python programming

Learn how to set up the Raspberry Pi environment with Raspbian and Linux OS. Write, Execute build application with SenseHaT. Use Python IDE for Raspberry Pi. Develop and debug using python on Raspberry Pi.

Key topics: Raspberry Pi platform configuration, OS installation, Linux Filesystems, Linux GUI and text editors, Python on Raspberry Pi Accessing libraries : GPIO,PWM,I2C etc.

Course 4: Raspberry Pi: Interface with Outside World

Learn how to use protocols like HDMI, USB, and Ethernet with external devices like sensors, Motors, GPS, Orientation, LCD, and SenseHAT to get your IoT devices interact with real world.

Key topics: Network & Secure shell, SSH client/server, Network Programs, Internet Protocols, TCP vs IP, Sockets, Python client/Server, Network libraries, Web services, Public APIs, Camera Integration and capturing images on Raspberry pi.

Course 5: Dragon Board & 96 Board Mezzanines

Learn to build IoT application on Qualcomm’s Dragon Board with 96 board mezzanines. Run Linaro Debian on it and build various interesting use cases of IoT.

Key topics: DragonBoard, Building OS on dragon Board, Linux/Android/Windows 10 IoT core set up on Dragon. Sensors and actuators and Camera Integration on DragonBoard.

Course 6: MQTT and IoT

Learn IoT specific Network protocols particularly MQTT protocols and develop a MQTT client using python.

Key topics: MQTT messaging protocol, MQTT hosting, Brokers and Servers, IoT dashboards, Node-RED

Module 3: IoT- Cloud computation & Integration with Amazon Web services

Course 1: Development on Amazon Web services (AWS)

Learn How to create and Manage AWS account. Install and use AWS SDKs. Get expertise to use AWS compute services.

Key topics: AWS services: RDS, Rekognition, EC2, AWS lambda, Amazon S3, AWS SNS, AWS CLI, AWS cloud9 and AWS IoT hub.

Course 2: Build your IoT application using AWS IoT hub.

Learn how to register, certify and create policies for your device using AWS IoT hub. Develop an end to end IoT application using AWS IoT SDKs and python script.

Key topics: Authentication and authorization of devices, Paho MQTT client, Publish & subscribe library, Amazon SNS, AWS python SDKs.

Course 3: IoT application using AWS SDKs and DragonBoard

Demonstrate various real world IoT use cases using AWS compute applications and DragonBoard. Live Demo of projects and conceptualisation of Capstone Project.

Key topics: AWS SDKs on DragonBoard, Template recognition and vision Intelligence. Voice recognition, Natural language processing and Text to speech based application demo.

Module 4: IoT- Cloud computation & Integration with Microsoft Azure

Course 1: Introduction to Azure IoT

Understand Azure IoT reference architecture. Learn to implement C2D and D2C messaging and review basic-device programming using Azure IoT device SDKs.

Key topics: Azure IoT hub, Azure IoT SDKs and tools, SDK demos, Gateway SDK, Device Management, IoT hub messaging, Security in IoT.

Course 2: IoT on Microsoft Azure

Learn how to develop IoT use cases with Microsoft Azure technologies. Device registration, C2D & D2C messaging. Real time monitoring of data through Azure Stream Analytics. Storage of sensor data in the cloud using Document DB. Data visualization using Powerbase features and add remote management capabilities to your device

Key topics: Azure IoT hub and Raspberry Pi, Node-Red with Azure, Data analysis with stream Analytics, Data storage and visualization. PowerBI, Firmware update through remote management, Capstone Project.

Module 5: IoT- Cloud computation & Integration with IBM Watson

Course 1: IoT application Development with IBM Watson

Learn to create a IoT solution by using IBM Watson cloud, Node-RED, Raspberry Pi and SenseHAT extension board.

Key topic: IBM Blue mix, Node-RED, Rapid application development in the cloud and on Raspberry Pi, Python API, MQTT in Watson IoT platform.

Course 2: IoT and Applied AI with Deep Learning (Advanced Course)

Learn Deep learning frameworks and develop analytics application by using Anomaly detection, Time Series Forecasting, Image Recognition and Natural Language processing on your IoT data.

Key topics: Keras, TensorFlow, PyTorch, Apache System ML.

Program Highlights

100 Hours – Classroom Training

IIT Alumni as Faculty

Real life use case simulations

Relevant Industry Experience

Hands-on Training | Capstone Project

Quality Content

Placement Assistance

Certificate of Excellence

[]
1 Step 1

I’m Interested in This Program

First Nameyour first name
Last Nameyour last name
MobileYour Mobile
tablet_mac
Previous
Next

What You’ll learn:

  • Networks, protocols and basic software for the Internet of Things (IoT)
  • How automated decision and control can be done with IoT technologies
  • Discuss devices including sensors, low power processors, hubs/gateways and cloud computing platforms
  • Learn about the relationship between data science and natural language and audio-visual content processing
  • Review fundamental techniques for visual feature extraction, content classification and high-dimensional indexing
  • Techniques that can be applied to solve problems in web-scale image search engines, face recognition, copy detection, mobile product search, and security surveillance
  • Examine data collection, processing and analysis
shadow