Abstract
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.
Original language | English |
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Title of host publication | Proceedings of the 9th Baltic Mechatronics Symposium |
Publisher | Aalto-yliopisto |
Number of pages | 6 |
ISBN (Electronic) | 978-952-64-9656-6 |
Publication status | Published - 2024 |
MoE publication type | A4 Conference publication |
Event | Baltic Mechatronics Symposium - Tallinn, Estonia Duration: 3 May 2024 → 3 May 2024 Conference number: 9 |
Conference
Conference | Baltic Mechatronics Symposium |
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Country/Territory | Estonia |
City | Tallinn |
Period | 03/05/2024 → 03/05/2024 |
Keywords
- accelerometer
- temperature measurement
- GPS
- wearable sensors
- dog behaviour