Introduction to IoT with Edge Devices, Sensors & S/Protocols

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Learn IoT with Edge Devices, Sensors and Real-World Applications in Smart Cities, Industrial Automation & Robotics

What you will learn


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Understand the difference between IoT, Edge Computing and Edge Machine Learning

Explore the different types of Input & Output Devices

Recognize the different type of pins on an Edge device – Power, Analog, Digital & PWM

Understand the working of an Analog-to-Digital-Converter (ADC)

Deep dive into the working of different serial protocols – UART, SPI and I2C

Delve into the working and real-world use cases of 9 different sensors – vision, humidity, radiation, gas etc.

Compare & contrast 5 popular edge devices like Arduino Nano 33 BLE Sense, Raspberry Pi 5 etc.

Explore TinyML and understand how it differs from Edge Machine Learning

Add-On Information:

  • Embark on a foundational journey into the Internet of Things (IoT), gaining a comprehensive grasp of how connected devices seamlessly integrate into our physical world.
  • Acquire proficiency in the core architecture of IoT systems, from data acquisition at the “edge” to processing and communication pathways.
  • Master the selection and interfacing of diverse sensor technologies, understanding their unique capabilities for capturing environmental and physical data.
  • Demystify the role of edge devices as intelligent gateways, capable of local data processing and decision-making before transmission.
  • Develop practical skills in connecting and communicating with embedded systems using industry-standard serial protocols, ensuring efficient data flow.
  • Gain hands-on experience with popular microcontrollers and single-board computers, learning to program and deploy them for specific IoT tasks.
  • Explore the principles of real-time data acquisition and manipulation, essential for responsive and dynamic IoT applications.
  • Understand the security considerations inherent in IoT deployments and learn best practices for safeguarding connected systems and data.
  • Appreciate the impact of IoT on transforming industries, with a focus on practical examples in smart cities, industrial automation, and robotics.
  • Discover the potential of leveraging machine learning algorithms directly on edge devices for intelligent automation and predictive capabilities.
  • Foster an innovative mindset to conceptualize and prototype your own IoT solutions for real-world challenges.
  • Understand the concept of a distributed computing paradigm where data is processed closer to the source, reducing latency and bandwidth usage.
  • Grasp the fundamental principles of creating interactive systems that respond to environmental stimuli.
  • Learn to differentiate between various communication paradigms used in IoT for device-to-device and device-to-cloud interactions.
  • PROS:
  • Build practical, hands-on experience with current IoT hardware and software.
  • Develop skills directly applicable to high-demand fields like automation and smart technology.
  • CONS:
  • A basic understanding of programming is beneficial for optimal learning, although not strictly required.
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