Implementing A Low-Power Sensor Node Network
In the current age of pervasive computing, the most common processing platforms are not computers anymore, but tiny, embedded microcontrollers. Leveraging these platforms for distributed computing is a topic of on-going research. One of the key issues in enabling deployment of such Internet of Things devices is communication. While many key technologies ranging from Low-Energy Bluetooth to LoRa have been proposed, there is still a lack of low-power optimized demonstrator platforms.
In this project, a sensor node platform with long-range communication will be developed. Starting from existing designs that integrate LoRa, the student's task is to integrate an embedded camera module and design a PCB to host all of the components. Depending on the student's progress, further tasks are to acquire an in-field dataset and training of a CNN to detect activity.
The student is required to:
- Read up on the LoRa protocol
- Deploy the protocol with a gateway
- Attach an embedded camera
- Design a PCB that hosts all components
- Prepare a demo
Depending on the progress, the following points may be investigated:
- Acquistion of a dataset
- Training and deployment of an energy-proportional CNN
- Basic knowledge of the C language and embedded system programming
Skills you might find useful, but are not required:
- Previous experience with the LoRa stack
- PCB Design with Altium
- Machine learning with Python
- Neural network deployment on embedded devices (Machine Learning on Microcontrollers)
Possible to complete as a Master, Semester or Bachelor Thesis
Meetings & Presentations
The students and advisor(s) agree on weekly meetings to discuss all relevant decisions and decide on how to proceed. Of course, additional meetings can be organized to address urgent issues. At the end of the project, you have to present/defend your work during a 15 min. presentation and 5 min. of discussion as part of the IIS colloquium.