Industrial Training IoT (Internet of Things) with Raspberry PI and AWS IoT Core Training Course

Module 0: Foundations & AWS IoT Ecosystem

• Introduction to IoT
  • Defining IoT in 2024: Beyond "Things" (Edge Intelligence, AI/ML at the Edge, Cyber-Physical Systems).
  • Factors driving IoT growth across industries and use cases.
  • Major IoT trends, including Edge Computing, Sustainability, AI/ML integration, and Enhanced Security.
  • AWS IoT's position within the broader AWS ecosystem (including AWS Partner Network - APN resources).
• Overview of the AWS IoT Service Landscape
  • AWS IoT Core (covering MQTT/Bridge, Jobs, and Device Defender).
  • AWS IoT Device Management (Device Onboarding, Configuration Management, and OTA Updates).
  • AWS IoT Analytics (focused on data processing, enrichment, and modeling).
  • AWS IoT Greengrass (enabling edge compute, local execution, and secure connectivity).
  • AWS IoT Button (providing a conceptual overview for simple device implementations).
  • Connections: Linking AWS IoT Core with > Lambda, DynamoDB, OpenSearch, Step Functions, and SageMaker.

Module 1: IoT Architecture, Components & Security

• IoT Architecture
  • Device Layer (incorporating Sensors, Actuators, and Edge Devices such as Raspberry Pi and ESP32).
  • Connectivity Layer (utilizing MQTT, CoAP, HTTP, and LPWAN standards like LoRaWAN, NB-IoT, Sigfox, and Cellular IoT).
  • Cloud Integration Layer (integrating AWS IoT Core, API Gateway, Lambda, and Step Functions).
  • Data Processing & Analytics Layer (employing DynamoDB, Timestream, OpenSearch, S3, Athena, and SageMaker).
  • Application Layer (developing Mobile and Web Apps using AWS Amplify, along with Custom Business Applications).
  • Significance: Explaining the rationale behind distributed architectures regarding latency, bandwidth, compute power, and security.
• In-depth Analysis of Essential IoT Components
  • Hardware: Selection criteria (MCU, connectivity, sensors) and Security elements (Trusted Execution Environments - TEEs).
  • Edge Computing (AWS Greengrass): Highlighting benefits such as low latency, reduced cloud traffic, and local decision-making capabilities.
  • Device Management: Covering Onboarding (Over-the-Air - OTA, Pre-provisioning), Configuration, Monitoring, and Remote Debugging.
  • Security Deep Dive: Addressing Device Identity, Authentication & Authorization (X.509 Certs, JSON Web Tokens - JWTs), Data Encryption (at rest and in transit), and AWS IoT Device Defender.
  • Security Standardization: Introducing industry standards (e.g., IEEE P2145, Open Connectivity Foundation - OCF) and compliance frameworks (ISO/IEC 27001, SOC 2).
• AWS-Specific PaaS Functions for IoT
  • AWS IoT Core (facilitating Secure MQTT/Bridge, firmware update Jobs, and Device Defender).
  • AWS Lambda (providing serverless compute for data preprocessing and action triggering).
  • AWS Step Functions (managing stateful workflows for complex device interactions).
  • Amazon DynamoDB (serving as a NoSQL database for rapid IoT data ingestion).
  • Amazon OpenSearch Service (supporting Search, Analytics, and Time Series data handling).
  • Amazon Timestream (acting as a specialized time-series database).
  • Amazon S3 (used for raw data lake storage).
  • AWS IoT Device Defender (for continuous monitoring and security assessment).
  • AWS IoT Wireless (enabling connectivity for remote LPWAN devices).

Module 2: IoT Device Communication Protocols

• MQTT (MQTT v5 & WebSockets)
  • MQTT 5.0 Features (including Retain, Clean Session flags, User Properties, and Wildcard topics).
  • MQTT over WebSockets (standardization aspects).
  • Explanation of Quality of Service (QoS) Levels.
  • Protocol Best Practices.
• Alternative Protocols
  • CoAP (Constrained Application Protocol) suitable for constrained devices.
  • AMQP / MQTT over AMQP (standard data interchange formats).
  • HTTP (ideal for simpler, less frequent updates).
  • WebSockets (enabling full-duplex communication).

Module 3: Building Robust IoT Applications with AWS

• Device Onboarding & Secure Connectivity
  • AWS IoT Device Defender Pre-Provisioning.
  • Secure Over-The-Air (OTA) Onboarding (e.g., leveraging AWS IoT Button concepts).
  • Managing Device Certificates (via ACM/PKI).
  • Implementing MQTT with TLS encryption.
• Data Ingestion, Storage & Processing
  • Efficiently transmitting data from devices to AWS IoT Core.
  • Selecting the appropriate targets: Lambda (event-driven), Step Functions (orchestration), Timestream (time-series), OpenSearch (search & analytics), or S3 (raw data).
  • Utilizing AWS IoT Analytics for data enrichment and cleansing prior to storage.
  • Managing high-throughput scenarios (using Kinesis/Firehose).
• Device Management & Operations
  • Leveraging AWS IoT Device Management for fleet management purposes.
  • Implementing and managing OTA Updates (using AWS IoT Jobs).
  • Conducting Remote Monitoring and Configuration.
• Building the IoT Backend
  • Using API Gateway to create REST/GraphQL APIs for interacting with devices and data.
  • Employing AWS Lambda for business logic execution.
  • Utilizing AWS Step Functions for coordinating distributed components.
  • Implementing Amazon SQS/SNS for asynchronous messaging and event triggering.

Module 4: Edge Computing & Advanced Integration

• AWS IoT Greengrass
  • Core concepts (Core, Device, and Connector components).
  • Executing Lambda functions locally on the device.
  • Running code directly on the device (in C++ or Python).
  • Establishing secure communication between Greengrass Core and AWS/IoT devices.
  • Use Case: Performing local data filtering, preprocessing, or AI inference at the edge.
• Integration with AI/ML
  • Using SageMaker for complex ML model deployment in the cloud.
  • Executing ML inference on the edge with Greengrass ML Accelerator (GMA).
• Data Visualization & User Interfaces
  • Leveraging AWS IoT SiteWise for industrial data visualization.
  • Building Web Apps using AWS Amplify (covering API, UI, and Authentication).
  • Creating dashboards using Amazon QuickSight or OpenSearch Dashboards.

Module 5: Security, Governance & Best Practices

• IoT Security Lifecycle
  • Secure Design Principles (focusing on Defense-in-Depth).
  • Secure Development Practices (referencing OWASP IoT Top 10).
  • Vulnerability Management strategies.
  • Threat Modeling specifically for IoT environments.
• AWS Security Services for IoT
  • AWS IoT Device Defender (covering both Service & Device Defender functionalities).
  • Integrating AWS Shield and AWS Identity and Access Management (IAM).
  • Utilizing AWS Config for compliance checks.
  • Integration of Hardware Security Modules (HSMs).
• Data Privacy & Governance
  • Handling sensitive data (including PII).
  • Establishing Data Retention and Deletion policies.
  • Addressing Compliance considerations.

Module 6: Hands-on Projects & Capstone

• Guided Hands-on Labs
  • Device Onboarding & MQTT Communication exercises.
  • Implementing Secure Data Ingestion to AWS.
  • Building a Simple IoT Dashboard.
  • OTA Update Simulation.
  • Introduction to AWS IoT Greengrass.
• Capstone Project
  • Developing a complete IoT solution addressing a real-world problem (e.g., Smart Home Automation, Environmental Monitoring, or Industrial Sensor Hub).
  • Requirements: Ensuring secure device implementation, data ingestion, processing, visualization, and optional edge components.
  • Utilizing the AWS services covered throughout the course.