Module 1: Introduction to IoT 

• Overview of IoT 
  • What is IoT? 
  • History and evolution of IoT. 
  • IoT applications in different industries. 
• IoT Architecture 
  • Layers of IoT: Perception layer, network layer, application layer. 
  • IoT system components: Sensors, actuators, gateways, and cloud services. 
• IoT Communication Models  
  • Device-to-device (D2D). 
  • Device-to-cloud (D2C).
  • Device-to-gateway (D2G). 
• IoT Standards and Protocols 
  • Common IoT protocols: MQTT, CoAP, HTTP. 
  • IoT data formats: JSON, XML, and CBOR. 

Module 2: IoT Hardware and Devices 

• Introduction to IoT Hardware
  • Types of sensors and actuators.
  • Popular IoT devices: Raspberry Pi, Arduino, ESP8266, ESP32

• Microcontroller Programming  (Optional – will consider with Embedded Training) 
  • Basics of microcontrollers (e.g., Arduino, ESP32). 
  • Programming for IoT using C/C++.

• Connecting Sensors to IoT Devices 
  • Interfacing sensors: Temperature, humidity, motion, pressure, light, etc.
  • ADCs, digital vs. analog signals.
  • Hands-on exercises: Building basic IoT devices. 

Module 3: IoT Communication and Networking 

• IoT Networking Basics 
  • IP addressing, DNS, and routing.
  • Overview of networking concepts: LAN, WAN, VPN, and protocols. 
• Wireless Communication in IoT
  • Wireless technologies: Wi-Fi, Bluetooth, Zigbee, LoRaWAN, NB-IoT, 5G
  • Pros and cons of each communication technology for IoT

• Network Protocols for IoT  (Optional – will consider with Embedded Training) 

• MQTT, CoAP, HTTP.
• Device-to-Device communication.
• Practical applications of IoT communication. 

Module 4: Cloud Computing for IoT

• Introduction to Cloud Computing

• Cloud services: IaaS, PaaS, SaaS.
• Benefits of cloud computing for IoT. 

• Cloud Platforms for IoT

• AWS IoT, Microsoft Azure IoT, Google Cloud IoT.
• Integrating IoT devices with cloud platforms. 

• Data Storage and Analysis in the Cloud

• Data storage options: Relational vs. NoSQL databases.
• Cloud analytics: Big Data and Machine Learning for IoT data analysis. 
• Hands-on: Sending data from devices to the cloud and analysing it. 

(Depending on the Cloud Platform availability) 

Module 5: IoT Security and Privacy

• Introduction to IoT Security

• Security challenges in IoT: Device, network, and data security. 
• Authentication and authorization mechanisms. 

• Best Practices and IoT Privacy

• Privacy concerns in IoT systems.
• Securing IoT data and devices.
• Case studies of IoT security breaches. 

Module 6: IoT Data Analytics and Visualization

• Introduction to Data Analytics in IoT

• Importance of data in IoT.
• Real-time vs. batch data processing. 

Module 7: IoT Software and Application Development 

• IoT Software Development

• Development of IoT applications: Mobile apps, Web interfaces. 

• Building IoT Applications

• Building a simple IoT application from scratch (Example of Node MCU).
• Connecting sensors, cloud, and mobile app for a complete IoT solution. 

Module 8: IoT Project and Case Studies 

• IoT Project Overview

• How to plan, design, and implement an IoT project. 
• Real-world IoT case studies and solutions. 

• Hands-on IoT Project
  • Students will build an IoT project (e.g., smart home system, remote monitoring system, etc.).
  • Project planning, sensor integration, cloud setup, and app development. 

Module 9: Emerging Trends in IoT

• Industry 4.0 and IoT
  • IoT in manufacturing, smart factories, and automation. 

• IoT and AI/ML
  • Leveraging Artificial Intelligence and Machine Learning in IoT systems. 

• Future of IoT 
  • IoT and 5G. 

• IoT in Smart Cities, Healthcare, and Transportation.