Tech for IoT (Internet of Things)

Navigating the Technical Landscape of the Internet of Things

Welcome to Tech for IoT, your go-to resource for delving into the technical intricacies of the Internet of Things (IoT).

This section provides in-depth insights into various facets of IoT, ranging from fundamental concepts like sensors and platforms to advanced discussions on IoT architecture and development.

Whether you’re a seasoned developer, an aspiring IoT enthusiast, or someone simply curious about the technical underpinnings of IoT, this page is designed to be your comprehensive guide.

Tech for IoT

Unraveling the Tech for IoT

  • What is Internet of Things
    Explore the foundational concepts of IoT, understanding the essence of a world where devices seamlessly communicate and collaborate.
  • Sensors and Actuators:
    • Dive into the world of sensors, the eyes and ears of IoT devices, and actuators, the components responsible for turning digital decisions into physical actions.
  • IoT Platforms:
    • Uncover the significance of IoT platforms as the backbone of IoT ecosystems, facilitating device communication, data management, and application development.
  • Connectivity Protocols:
    • Delve into the various communication protocols that enable devices to connect and exchange data, from standard Wi-Fi and Bluetooth to specialized low-power alternatives.
  • IoT Architecture:
    • Understand the architectural principles governing the design and deployment of robust IoT solutions, including edge computing and cloud-based approaches.
  • Security in IoT:
    • Navigate the complex landscape of IoT security, exploring strategies and best practices to safeguard devices, data, and communication channels.
  • IoT Development Tools:
    • Equip yourself with the tools and frameworks essential for developing IoT applications, from integrated development environments (IDEs) to simulation platforms.
  • Case Studies:
    • Explore real-world applications of IoT, dissecting successful implementations across industries such as healthcare, agriculture, and smart cities.

Domain Expertise areas in Tech for Internet of Things :

The Internet of Things is a vast subject that required multiple domain expertise for end to end system to work flawlessly. However it might not be possible for one person to be expert in all these tech for IoT, however for a successful IoT system to work we might need experts from multiple domains. A list of such domains is shared below –

  • Computer Science
    • Backend Development (for IoT Platform Development)
      • Java
      • Springboot
    • Frontend Development (for IoT Platform Development)
      • Javascript
      • HTML CSS
      • React
      • Angular
      • Vue
    • Firmware Development (for IoT Device Firmware Development)
      • Python
      • C
      • C++
    • System Administration
      • Linux
      • Windows
    • Database
      • MySQL
      • Mongo DB
      • Bigdata
    • Cloud computing
      • AWS
      • Azure
      • Google Cloud Platform
    • Data Science and Analytics
      • Machine Learning
      • Big data Analytics
      • Data mining
    • Computer networking
    • Cybersecurity
    • Mobile App Development
    • Edge Computing
    • Distributed systems
    • Blockchain
    • Robotics
  • Electronics Engineering
    • Embedded systems
    • Sensors
    • Actuators
    • Communication systems
  • Electrical Engineering
    • PLC
    • SCADA
    • Human-Machine Interface (HMI)
    • Electrical Machines
    • Power System
    • Power Electronics
    • Instrumentation
    • Control Systems


You might be overwhelmed by the large number of skillsets that it takes to create a robust end to end IoT system, but please note that for a particular use case all these skillsets might not be required together. So take a deep breath.

If you ask what is the heart of Tech for IoT then it is Computer Networking, as IoT is about connecting the various sensors, actuators together through communication systems.

Then storing the data collected on a database.

Data Science and Analytics skillset is required to process the data.

There are decisions that are taken by the admin or by the algorithms.