Tiny embedded machine vision for metering (and beyond)

Supervisors: Sebastian B├╝ttrich
Semester: Fall 2022
Tags: IoT, sensors, machine learning, computer vision

There is currently a lot of progress in really small, yet powerful visual machine learning / computer vision, on hardware like the OpenMV Cam H7, Arduino Portenta Vision Shield, Luxonis LUX-ESP32, Himax WE-I Plus, Arducam Pico4ML, and Raspberry Pi, and on software platforms such as TinyML or OpenMV IDE.

While many popular use cases stem from fields like traffic analysis, wildlife monitoring, we propose to explore the potential of these techniques for a seemingly simple, yet very important field: the retrofitting of leagcy meters and displays, i.e. appliances lacking any digital data interfaces.

Ideally, small low power inexpensive computer vision systems should be

- capabale of recognizing what kind of display they are dealing with
- working even under difficult light conditions
- able to coexist with manual reading (i.e. not blocking the display)

legacy manometers image