The explosion of embedded and connected smart devices, systems and technologies in our lives has created an opportunity to connect every ‘thing’ to the internet. The resultant data collection and connectivity has created efficiencies and solutions previously dreamt up only in science fiction stories.

IoT systems allow users to achieve deeper automation, analysis, and integration within a system. They improve the reach of these areas and their accuracy. IoT utilizes existing and emerging technology for sensing, networking, and robotics.

The most important features of IoT include artificial intelligence, connectivity, sensors, active engagement, and small device use.

The hardware utilized in IoT systems includes devices for a remote dashboard, devices for control, servers, a routing or bridge device, and sensors. These devices manage key tasks and functions such as system activation, action specifications, security, communication, and detection to support-specific goals and actions and the most important hardware in IoT might be its sensors. These devices consist of energy modules, power management modules, RF modules, and sensing modules. RF modules manage communications through their signal processing, WiFi, ZigBee, Bluetooth, ultrasonic, PIR, Temperature, radio transceiver etc.

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This course deals with basic electronics, microcontroller architectures, sensors, human-machine interfaces (HMI) and basic networking. We use the Arduino platform to teach these concepts.
  • Getting Started with Arduino
  • Sensors, Signals & Electronics
  • Microcontroller Concepts
  • Basic Networking with Nodemcu
  • Advanced Microcontroller Concepts
This course provides an overview and insights into data generation, analysis, and usage from IOT systems, and uses multiple case studies to explain how analytics is used in IOT scenarios to accomplish desired outcomes. This course module explores diverse use cases of IOT across verticals including sports, healthcare etc.
  • IOT Reference Architecture
  • IOT Data Overview and Use Cases
  • IOT Data Reference Architecture & Platforms
  • Introduction to Machine Learning and Python
  • KPIs in IOT Analytics
  • Case Study/Project: Human Activity Recognition