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: Moving beyond simple "Things" to include Edge Intelligence, AI/ML at the Edge, and Cyber-Physical Systems.
  • Factors driving IoT growth across industries and specific use cases.
  • Leading IoT trends such as Edge Computing, sustainability, AI/ML integration, and enhanced security.
  • The position of AWS IoT within the wider AWS ecosystem, including resources from the AWS Partner Network (APN).
• Overview of the AWS IoT Service Landscape
  • AWS IoT Core, covering MQTT/Bridge, Jobs, and Device Defender.
  • AWS IoT Device Management, including device onboarding, configuration management, and OTA updates.
  • AWS IoT Analytics for data processing, enrichment, and modeling.
  • AWS IoT Greengrass for edge compute, local execution, and secure connectivity.
  • AWS IoT Button as a conceptual overview for simple devices.
  • Integration Point: Connecting AWS IoT Core to Lambda, DynamoDB, OpenSearch, Step Functions, and SageMaker >.

Module 1: IoT Architecture, Components & Security

• IoT Architecture
  • Device Layer: Sensors, actuators, and edge devices such as Raspberry Pi and ESP32.
  • Connectivity Layer: Protocols like MQTT, CoAP, HTTP, and LPWAN technologies including LoRaWAN, NB-IoT, Sigfox, and Cellular IoT.
  • Cloud Integration Layer: Services like AWS IoT Core, API Gateway, Lambda, and Step Functions.
  • Data Processing & Analytics Layer: DynamoDB, Timestream, OpenSearch, S3, Athena, and SageMaker.
  • Application Layer: Mobile and web apps built with AWS Amplify, along with custom business applications.
  • Significance: Understanding the rationale behind distributed architectures regarding latency, bandwidth, compute power, and security.
• In-Depth Look at Essential IoT Components
  • Hardware: Selection criteria (MCU, connectivity, sensors) and security elements like Trusted Execution Environments (TEEs).
  • Edge Computing (AWS Greengrass): Advantages such as low latency, reduced cloud traffic, and local decision-making.
  • Device Management: Onboarding (via Over-the-Air (OTA) or pre-provisioning), configuration, monitoring, and remote debugging.
  • Security Deep Dive: 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: Overview of standards (e.g., IEEE P2145, Open Connectivity Foundation (OCF)) and compliance frameworks (ISO/IEC 27001, SOC 2).
• IoT-Specific PaaS Functions in AWS
  • AWS IoT Core for secure MQTT/Bridge, firmware update Jobs, and Device Defender.
  • AWS Lambda for serverless compute in data preprocessing and action triggering.
  • AWS Step Functions for stateful workflows managing complex device interactions.
  • Amazon DynamoDB as a NoSQL database for rapid IoT data ingestion.
  • Amazon OpenSearch Service for search, analytics, and time-series data handling.
  • Amazon Timestream as a specialized time-series database.
  • Amazon S3 for raw data lake storage.
  • AWS IoT Device Defender for monitoring and security assessment.
  • AWS IoT Wireless for connecting remote LPWAN devices.

Module 2: IoT Device Communication Protocols

• MQTT (MQTT v5 & WebSockets)
  • Features of MQTT 5.0, including Retain, Clean Session flags, User Properties, and Wildcard topics.
  • Standardization of MQTT over WebSockets.
  • Explanation of Quality of Service (QoS) levels.
  • Best practices for protocol implementation.
• Alternative Protocols
  • CoAP (Constrained Application Protocol) designed for constrained devices.
  • AMQP and MQTT over AMQP for standard data interchange formats.
  • HTTP for simpler, less frequent update scenarios.
  • WebSockets for full-duplex communication.

Module 3: Building Robust IoT Applications with AWS

• Device Onboarding & Secure Connectivity
  • Pre-Provisioning with AWS IoT Device Defender.
  • Secure Over-The-Air (OTA) onboarding, leveraging concepts from AWS IoT Button.
  • Management of device certificates using ACM/PKI.
  • Implementation of MQTT with TLS for secure transmission.
• Data Ingestion, Storage & Processing
  • Efficiently transmitting data from devices to AWS IoT Core.
  • Selecting 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 oversight.
  • Implementing and managing OTA Updates via AWS IoT Jobs.
  • Performing remote monitoring and configuration adjustments.
• Developing the IoT Backend
  • Using API Gateway to create REST/GraphQL APIs for interacting with devices and data.
  • Employing AWS Lambda for business logic execution.
  • Using AWS Step Functions to coordinate distributed components.
  • Utilizing Amazon SQS/SNS for asynchronous messaging and event triggering.

Module 4: Edge Computing & Advanced Integration

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

Module 5: Security, Governance & Best Practices

• IoT Security Lifecycle
  • Principles of secure design, specifically Defense-in-Depth.
  • Secure development practices, referencing the OWASP IoT Top 10.
  • Strategies for vulnerability management.
  • Threat modeling techniques for IoT systems.
• AWS Security Services for IoT
  • Overview of AWS IoT Device Defender (Service and Device Defender).
  • Implementation of AWS Shield and AWS Identity and Access Management (IAM).
  • Using AWS Config for compliance verification.
  • Integration with Hardware Security Modules (HSMs).
• Data Privacy & Governance
  • Handling sensitive data, particularly Personally Identifiable Information (PII).
  • Policies for data retention and deletion.
  • Considerations for regulatory compliance.

Module 6: Hands-on Projects & Capstone

• Guided Practical Labs
  • Device Onboarding and MQTT Communication setup.
  • Implementing secure data ingestion to AWS.
  • Constructing a basic IoT dashboard.
  • Simulating an OTA Update process.
  • Familiarization with AWS IoT Greengrass.
• Capstone Project
  • Develop a comprehensive IoT solution addressing a real-world issue, such as Smart Home Automation, Environmental Monitoring, or an Industrial Sensor Hub.
  • Requirements include a secure device, data ingestion, processing, visualization, and an optional edge component.
  • Application of AWS services covered throughout the course.