Description
Introduction
Edge IoT is transforming how data is processed and managed, bringing computation closer to where data is generated, enhancing response times, and reducing bandwidth usage. This course provides a comprehensive introduction to Edge IoT, focusing on its principles, key applications, and how it differs from traditional cloud-based IoT systems. Attendees will explore how Edge IoT enables real-time analytics, improves system efficiency, and supports the growing number of IoT devices in industries such as healthcare, manufacturing, and smart cities.
Prerequisites
- Basic understanding of IoT and cloud computing concepts
- Familiarity with network architectures
- Programming knowledge in languages such as Python or C++ is beneficial but not mandatory
- Understanding of sensors, embedded systems, and communication protocols (optional)
Table of Contents & Sessions
Session 1: Introduction to Edge Computing and IoT
- Overview of IoT architecture
- Traditional IoT vs. Edge IoT
- Benefits of Edge IoT: latency, bandwidth, and security
- Key applications of Edge IoT in different industries
- Challenges of Edge IoT
Session 2: Edge Computing Architecture
- The anatomy of an Edge device
- Distributed computing and its relevance to IoT
- Data processing: From sensor to edge
- Edge gateway and communication protocols (MQTT, CoAP)
- Cloud-Edge hybrid systems: When to use which
Session 3: Edge Devices and Hardware
- Overview of popular edge devices: Raspberry Pi, NVIDIA Jetson, etc.
- Sensors and actuators in Edge IoT
- Real-time data processing and local storage
- Power management in Edge IoT systems
- Case studies of hardware implementations
Session 4: Software in Edge IoT
- Operating systems for edge devices: Linux, RTOS
- Programming edge devices: Python, C++, and JavaScript
- Introduction to machine learning at the edge
- Managing Edge IoT devices remotely
Session 5: Networking and Communication in Edge IoT
- Key networking concepts for Edge IoT (LAN, WAN, 5G, etc.)
- Communication protocols used in Edge IoT
- Latency and bandwidth considerations
- Edge security: Securing the communication and device
Session 6: Data Management in Edge IoT
- Data filtering, processing, and storage at the edge
- Handling big data at the edge vs. the cloud
- Implementing AI and ML for real-time decision-making
- Edge-to-cloud integration for analytics
Session 7: Edge IoT Security
- Overview of security risks in Edge IoT systems
- Data encryption, access control, and device authentication
- Edge device firmware and software security
- Case study: Security breaches in Edge IoT and lessons learned
Session 8: Case Studies and Real-World Applications
- Smart cities: Traffic management and surveillance systems
- Healthcare: Real-time patient monitoring
- Manufacturing: Predictive maintenance and automation
- Agriculture: Precision farming using edge analytics
- Future trends in Edge IoT applications
Session 9: Hands-on Project and Demo
- Setting up an edge computing environment with Raspberry Pi
- Connecting sensors and performing local data processing
- Building a simple edge-to-cloud solution
- Real-time monitoring and control using Edge IoT
- Group discussion and Q&A session
This structured course will help participants gain a solid foundation in Edge IoT concepts and how to implement real-world applications, addressing both technical and practical challenges
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