Introduction to IoT Course

Lesson 1 • How IoT Differs from the Regular Internet

Contrasts machine-to-machine communication with human-driven web interaction. Students articulate why IoT requires different design and infrastructure assumptions.

Lesson 2 • A Brief History of Connected Devices

Traces IoT from early RFID and M2M systems to today's smart ecosystems. Historical context helps students understand why current standards and challenges exist.

Lesson 3 • Core Components of an IoT System

Sensors, actuators, connectivity, and cloud platforms are identified as the four pillars of any IoT system. Students map these components to real-world device examples.

Lesson 4 • The IoT Ecosystem and Its Stakeholders

Maps the roles of device makers, platform providers, developers, and end users. Students recognise how stakeholder interests shape IoT product decisions.

Lesson 1 • Types of Sensors and What They Measure

Categorises sensors by physical phenomenon: temperature, motion, light, pressure, and more. Students match sensor types to appropriate use cases in everyday environments.

Lesson 2 • Microcontrollers and Single-Board Computers

Distinguishes microcontrollers from single-board computers by capability and power profile. Students identify which platform suits a given IoT application scenario.

Lesson 3 • Wired Connectivity Options

Covers Ethernet, serial protocols, and industrial fieldbus standards used in IoT deployments. Students evaluate when wired connections outperform wireless alternatives.

Lesson 4 • Wireless Connectivity Options

Surveys Wi-Fi, Bluetooth, Zigbee, Z-Wave, LoRa, and cellular for IoT use. Students compare range, bandwidth, and power trade-offs to select the right protocol.

Lesson 1 • Interoperability and Standards Bodies

Surveys standards from major IoT alliances and how they promote device compatibility. Students explain why fragmentation remains a challenge and how standards address it.

Lesson 2 • Data Formats: JSON, XML, and CBOR

Compares human-readable and binary data formats used in IoT payloads. Students evaluate format trade-offs for bandwidth, parsing speed, and readability.

Lesson 3 • HTTP, REST, and CoAP for IoT

Contrasts REST-based HTTP with the lightweight CoAP protocol designed for constrained networks. Students choose between them based on device capability and network conditions.

Lesson 4 • Why Protocols Matter in IoT

Explains how protocol choice affects reliability, power use, and interoperability. Students connect protocol decisions to real-world deployment outcomes.

Lesson 1 • Automation Rules and Scenes

Covers trigger-condition-action logic used to build home automation routines. Students design a multi-device automation scenario using if-then rule structures.

Lesson 2 • Voice Assistants and Natural Language Control

Explains how voice assistants act as IoT control interfaces using natural language processing. Students map the command path from spoken word to device action.

Lesson 3 • Evaluating Smart-Home Ecosystems

Compares major smart-home platforms on compatibility, privacy, and longevity. Students apply evaluation criteria to recommend a platform for a given household profile.

Lesson 4 • Common Smart-Home Device Categories

Catalogues lighting, thermostats, locks, cameras, and appliances as IoT device classes. Students identify the sensor and actuator roles within each category.

Lesson 1 • Supply Chain and Logistics IoT

Covers GPS tracking, cold-chain monitoring, and RFID in logistics operations. Students evaluate how real-time visibility reduces loss and improves delivery accuracy.

Lesson 2 • Industrial IoT Fundamentals

Defines IIoT and contrasts it with consumer IoT on reliability, safety, and scale. Students identify the operational technology layer and its integration with IT systems.

Lesson 3 • Operational Challenges at Scale

Addresses device management, firmware updates, and network reliability across thousands of nodes. Students propose strategies for maintaining large IoT deployments.

Lesson 4 • Smart-City Infrastructure Applications

Examines connected traffic, utilities, waste, and public safety systems in urban IoT. Students map city-scale sensor networks to resident quality-of-life outcomes.

Lesson 1 • Cloud Platforms for IoT Data

Surveys IoT-specific cloud services for ingestion, storage, and stream processing. Students map platform features to the requirements of a sample IoT application.

Lesson 2 • Basic Analytics and Anomaly Detection

Introduces statistical thresholds, moving averages, and rule-based anomaly detection. Students apply these techniques to identify abnormal sensor readings in a dataset.

Lesson 3 • Characteristics of IoT Data

Describes IoT data as high-volume, time-series, and often noisy or incomplete. Students apply this understanding to choose appropriate storage and processing strategies.

Lesson 4 • Dashboards and Data Visualisation

Covers real-time dashboards, historical trend charts, and alert panels for IoT data. Students design a dashboard layout for a smart-building energy monitoring scenario.

Lesson 1 • Encryption and Secure Communication

Explains TLS, DTLS, and end-to-end encryption for IoT data in transit and at rest. Students evaluate encryption options against device resource constraints.

Lesson 2 • Common IoT Attack Vectors

Catalogues default credentials, unencrypted traffic, insecure APIs, and firmware vulnerabilities. Students map each attack vector to a real-world IoT incident pattern.

Lesson 3 • Authentication and Access Control

Covers device identity, certificate-based authentication, and role-based access control. Students apply these controls to a smart-home or industrial IoT scenario.

Lesson 4 • Privacy Considerations and Data Governance

Addresses data minimisation, consent, retention limits, and user rights in IoT contexts. Students draft a basic data governance policy for a consumer IoT product.

Lesson 1 • Defining Requirements and Use Cases

Guides students through stakeholder interviews, functional requirements, and constraint mapping. Clear requirements prevent costly redesigns during later deployment phases.

Lesson 2 • Deployment, Testing, and Iteration

Covers staged rollout, functional testing, performance benchmarking, and post-deployment monitoring. Students create a deployment plan and define success metrics for their solution.

Lesson 3 • Designing the Data Pipeline

Structures the end-to-end data flow from device to dashboard using edge and cloud components. Students produce a data architecture diagram for their solution blueprint.

Lesson 4 • Security and Privacy by Design

Embeds authentication, encryption, and data governance into the solution from the start. Students annotate their blueprint with security controls at each architecture layer.