bharathsudharsan/OTA-TinyML
Code for IEEE Internet Computing Journal paper 'OTA-TinyML: Over the Air Deployment of TinyML Models and Execution on IoT Devices'
This project helps developers and engineers remotely update the machine learning models running on their Internet of Things (IoT) devices. Instead of physically reflashing each device, you can send new TinyML models over the internet from a web server. This allows IoT devices, even low-cost ones like ESP32 boards, to dynamically load and execute different ML models on demand, such as keyword spotting or anomaly detection.
No commits in the last 6 months.
Use this if you need to frequently update or change the machine learning models running on many resource-constrained IoT devices without physical access.
Not ideal if your IoT devices only ever run a single, static machine learning model that doesn't require remote updates.
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29
Forks
6
Language
C++
License
MIT
Category
Last pushed
Jul 07, 2022
Commits (30d)
0
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