Internet of Things (IoT) Development and Integration
Artificial Intelligence (AI)
COURSE OVERVIEW
This intensive five-day training program is designed to provide participants with a comprehensive understanding of the Internet of Things (IoT) ecosystem—from foundational concepts to hands-on implementation of connected systems. Learners will explore how physical devices communicate, how data is collected and processed in real time, and how IoT solutions are deployed using cloud platforms and modern analytics.
By the end of the course, participants will be able to design, build, secure, and deploy end-to-end IoT applications for real-world use cases such as smart homes, industrial automation, and smart cities.
COURSE OBJECTIVES
By the end of this course, participants will be able to:
- Understand core IoT principles, architectures, and ecosystem components.
- Identify and work with IoT sensors, actuators, and embedded devices.
- Configure communication protocols used in IoT systems (MQTT, HTTP, CoAP, etc.).
- Integrate IoT devices with cloud platforms for data storage and processing.
- Apply edge computing concepts for real-time IoT data handling.
- Analyze IoT data using basic analytics and visualization techniques.
- Implement security best practices for IoT devices and networks.
- Build and deploy a working IoT-based application as a final project.
Duration: 5 Days / 40 Hours
Delivery Method: Classroom-based, Virtual Instructor Led Training
COURSE OUTLINE
Day 1: Introduction to Internet of Things (IoT)
Focus: Understanding IoT fundamentals and ecosystem
- Evolution of IoT: From embedded systems to connected ecosystems
- IoT fundamentals and key concepts
- IoT architecture layers (Perception, Network, Processing, Application)
- Overview of IoT devices, sensors, and actuators
- Types of IoT applications (Smart home, healthcare, industry, agriculture)
- Introduction to communication protocols (MQTT, HTTP, CoAP, BLE)
- Hands-on: Setting up basic IoT simulation environment
Day 2: IoT Hardware and Connectivity
Focus: Understanding devices, embedded systems, and networking
- Overview of microcontrollers (Arduino, Raspberry Pi, ESP32)
- Basics of embedded systems and firmware concepts
- Sensor integration (temperature, motion, humidity, light sensors)
- Actuators and control systems
- IoT networking fundamentals (Wi-Fi, Bluetooth, Zigbee, LoRaWAN)
- Introduction to cloud connectivity for IoT devices
- Hands-on: Connecting sensors to a microcontroller and sending data
Day 3: IoT Data Processing and Analytics
Focus: Collecting, processing, and analyzing IoT data
- IoT data lifecycle: collection, transmission, processing, storage
- Edge computing vs Cloud computing in IoT systems
- Real-time data processing concepts
- Introduction to IoT data analytics and visualization
- Stream processing basics (event-driven architecture)
- Time-series data in IoT applications
- Hands-on: Visualizing sensor data in real time dashboard
Day 4: IoT Security and Cloud Integration
Focus: Securing and integrating IoT systems with cloud platforms
- IoT security challenges and vulnerabilities
- Device authentication and secure communication
- Data encryption and secure transmission protocols
- IoT device management and lifecycle management
- Cloud IoT platforms overview (AWS IoT, Azure IoT, Google Cloud IoT)
- Integration of IoT devices with cloud services
- Introduction to AI and IoT convergence (Smart systems)
- Hands-on: Connecting IoT device to cloud dashboard
Day 5: IoT Project Implementation and Deployment
Focus: Building and presenting a complete IoT solution
- Designing a complete IoT system architecture
- Smart IoT application development (use case selection)
- Integration of hardware, software, and cloud components
- Testing and troubleshooting IoT systems
- Deployment strategies for IoT solutions
- Final capstone project development
- Project presentation and evaluation
- Future trends in IoT (5G IoT, Smart Cities, Industrial IoT)
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