Multi-Sensor Wearable Device for Health Monitoring and Analysis in Canines

Eric Mizukami, Krishan Chamalka, Muhammad Ahmad, Sai Chandrresh, Panu Kiviluoma, Petri Kuosmanen

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

Abstrakti

Ensuring the well-being of our canine companions is paramount nowadays and this study presented a wearable device with built in motion sensors, GPS tracking and temperature monitoring capabilities and hence offered a novel method of monitoring canine health. Through the collection and analysis of extensive data on location, physical activity, and body temperature, the device provided pet owners with insightful information about the health of their dogs. Through the combination of sensor data and machine learning algorithm facilitated in early detection of potential health issues by predicting activities such as walking and sleeping. Experimental results showed that, device could predict sleeping and walking with an accuracy 87%. The proposed device represented a promising tool for promoting canine health surveillance and responsible pet ownership.
AlkuperäiskieliEnglanti
OtsikkoProceedings of the 9th Baltic Mechatronics Symposium
KustantajaAalto-yliopisto
Sivumäärä6
ISBN (elektroninen)978-952-64-9656-6
TilaJulkaistu - 2024
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaBaltic Mechatronics Symposium - Tallinn, Viro
Kesto: 3 toukok. 20243 toukok. 2024
Konferenssinumero: 9

Conference

ConferenceBaltic Mechatronics Symposium
Maa/AlueViro
KaupunkiTallinn
Ajanjakso03/05/202403/05/2024

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