3.7 KiB
3.7 KiB
layout, title, categories, tags, excerpt, header, role, skills, duration
| layout | title | categories | tags | excerpt | header | role | skills | duration | ||
|---|---|---|---|---|---|---|---|---|---|---|
| single | IoT Practical Exercise | teaching | teaching iot mqtt python influxdb distributed-systems practical-course | Designed/taught IoT practical (MQTT, Python) for ~200 students. |
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Practical Course Instructor/Designer | Curriculum Design (Practical Exercise), IoT Protocols (MQTT), Time Series Databases (InfluxDB), Python Programming, Live Coding, Large Group Instruction | Winter Semester 2018/19 |
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As part of the lecture Internet of Things (IoT): Devices, Connectivity, and Services, I was responsible for designing and conducting a practical programming exercise suitable for completion within one to two class sessions. This exercise targeted approximately 200 students during the Winter Semester 2018/19.
The goal was to provide hands-on experience with fundamental IoT communication patterns. The chosen approach involved:
- Communication Protocol: Implementing a typical publish/subscribe system using the MQTT protocol.
- Data Persistence: Storing simulated sensor data in an InfluxDB time-series database backend.
- Sensor Simulation: Generating high-frequency data streams to mimic real-world sensor behavior.
- Implementation Language: Requiring students to implement the entire pipeline from scratch using Python. Foundational Python skills were covered in a separate preparatory course.
The exercise aimed to solidify theoretical concepts discussed in the main lecture by applying them in a practical, albeit simulated, IoT scenario.
Associated Lecture Topics
- Arduino and Raspberry Pi
- Wearables & Ubiquitous Computing
- Edge/Fog/Cloud Computing
- Scalable Algorithms
- Spatial Data Mining
- Blockchain & Digital Consensus
- Predictive Maintenance
- Smart IoT Applications
- Cyber Security
- Web of Things
Practical Exercise Focus
The hands-on session concentrated specifically on:- Understanding the MQTT Publish/Subscribe pattern.
- Implementing MQTT clients (publishers/subscribers) in Python.
- Interfacing with InfluxDB for time-series data storage using Python libraries.
- Simulating basic sensor data streams.
- Integrating components into a functional pipeline.