Jan 18, 2024
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References
- 1. Vehkaoja, Antti; Somppi, Sanni; Törnqvist, Heini; Valldeoriola Cardó, Anna; Kumpulainen, Pekka; Väätäjä, Heli; Majaranta, Päivi; Surakka, Veikko; Kujala, Miiamaaria; Vainio, Outi (2021), “Movement Sensor Dataset for Dog Behavior Classification”, Mendeley Data, V1, doi: 10.17632/vxhx934tbn.1
- 2. Kumpulainen, P., Cardó, A. V., Somppi, S., Törnqvist, H., Väätäjä, H., Majaranta, P., Gizatdinova, Y., Hoog Antink, C., Surakka, V., Kujala, M. V., Vainio, O., & Vehkaoja, A. (2021). Dog behaviour classification with movement sensors placed on the harness and the collar. Applied Animal Behaviour Science, 241, 105393. https://doi.org/10.1016/j.applanim.2021.105393
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About This Project
Edge machine learning refers to the process of running embedded ML models on site using devices capable of collecting, processing, and recognizing patterns within collections of raw data. This project seeks to train one of such devices (Nicla SenseME) with dog data from the Earth Species' Bio-logger Ethogram Benchmark (BEBE). The board will be used as a smart dog collar, with its ML inferences controlling haptics vibrations in a bracelet wore by a person.
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