IOT & Edge Computing​

This course is designed to provide a thorough understanding of the Internet of Things (IoT) and Edge Computing. By the end of the course, participants will be proficient in IoT architectures, edge computing principles, IoT device management, and real-time data processing. This hands-on course covers theory, practical implementation, and case studies to ensure learners gain real-world skills.

Module 1: Introduction to IoT and Edge Computing (4 Hours)

• Overview of IoT:
  • Definition, components, and evolution
  • IoT applications across industries
• Edge Computing Basics:
  • What is Edge Computing?
  • Differences between IoT and Edge Computing
  • Benefits and challenges of Edge Computing

Module 2: IoT Architecture and Protocols (8 Hours)

• IoT System Architecture:
  • Device layer, Network layer, and Application layer
• IoT Protocols:
  • MQTT, CoAP, HTTP, and WebSockets
  • Hands-on with MQTT protocol
• Communication Technologies:
  • Wi-Fi, Zigbee, LoRa, and Cellular (4G, 5G)

Module 3: Sensors, Actuators, and IoT Devices (6 Hours)

• Understanding Sensors and Actuators:
  • Types of sensors (temperature, pressure, motion, etc.)
  • Actuators and control mechanisms
• IoT Devices:
  • Raspberry Pi, Arduino, ESP8266, etc.
  • Setting up a basic IoT project using Raspberry Pi

Module 4: Edge Computing Frameworks and Architecture (8 Hours)

• Edge Computing Architecture:
  • Edge vs. Cloud
  • Hybrid computing models
• Popular Edge Computing Frameworks:
  • AWS IoT Greengrass, Microsoft Azure IoT Edge, Google Cloud IoT Edge
• Edge Computing Use Cases:
  • Real-time decision-making, Industrial IoT, Smart Cities

Module 5: Data Processing in IoT and Edge Computing (8 Hours)

• Data Collection & Processing:
  • Sensors to data processing pipeline
  • Structured vs. unstructured data
• Data Analytics at the Edge:
  • Real-time data analytics at the edge
  • Edge AI: Machine Learning at the Edge
• Hands-on Lab:
  • Set up a local data processing system

Module 6: IoT Security and Privacy (6 Hours)

• Security Challenges in IoT:
  • Data privacy, device authentication, and encryption
• Security Solutions:
  • Blockchain for IoT, AI-powered security
  • Securing communication channels
• Edge Computing Security Concerns:
  • Managing data privacy at the edge
  • Hands-on: Setting up secure IoT devices

Module 7: IoT Platforms and Cloud Integration (6 Hours)

• Popular IoT Platforms:
  • AWS IoT Core, Microsoft Azure IoT Hub, Google IoT Core
• Cloud Integration for IoT:
  • How IoT systems interact with the cloud
  • Edge and cloud collaboration
• Hands-on:
  • Connecting IoT devices to a cloud platform

Module 8: IoT Analytics and Monitoring (6 Hours)

• IoT Data Analytics:
  • Predictive maintenance, operational efficiency
  • Visualization tools for IoT data (Grafana, Kibana)
• Monitoring IoT Devices:
  • Real-time monitoring, alerting, and performance optimization
• Hands-on Lab:
  • Implementing an IoT monitoring dashboard

Module 9: Project and Case Studies (6 Hours)

• Industry Use Cases of IoT and Edge Computing:
  • Smart cities, Industrial automation, Healthcare, and Transportation
• Group Project:
  • End-to-end IoT system design and implementation
  • Real-world problem-solving using IoT and Edge Computing
• Presentation and Assessment:
  • Showcase project outcomes