Competence idb (space) by T. Amberg & J. Luthiger for FHNW.
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The idb competence wants to enable you to use the physical world as a data source for your data analysis projects. In the end you will have a deeper unterstanding of:
- How to aquire data from the physical world?
- How to aggregate data in the field?
- How to transport data to a backend?
- How to access data on the backend for analysis?
- How tools/platforms differ and what are advantages and disadvantages?
To be able to compare the technologies used, it is essential that you have an understanding of the underlying concepts.
Resources and code examples to get into Internet of Things (IoT) data collection:
- Introduction - how to get started with CircuitPython, nRF52840 and Raspberry Pi.
- Data Acquisition - how to acquire measurement data from sensors.
- Data Transport - how to transport data to the backend.
- Data Analysis - how to display and analyse data.
For additional motivation try this mini-challenge:
- Hot cup sensor mini-challenge
The following modular hardware is available in your IoT kit:
- Raspberry Pi Zero W - a small Linux computer.
- Feather nRF52840 Express - a microcontroller.
- FeatherWing ESP32 AirLift - a Wi-Fi radio module.
- FeatherWing RFM95W - a LoRaWAN radio module.
- Grove Sensors & Actuators - to measure and control.
- Grove Adapters - to wire things up.
E.g. to build a battery-powered device with a sensor and connectivity:
For additional resources, check the IoT Data Collection Wiki:
Unless noted otherwise:
- Source code examples in this repository are declared Public Domain CC0 1.0
- Slides by T. Amberg & J. Luthiger are licensed under Creative Commons CC BY-SA 4.0
Publishing your own code?
- Choose an open source license, e.g. the simple MIT License