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

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

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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 languageEnglish
Title of host publicationProceedings of the 9th Baltic Mechatronics Symposium
PublisherAalto-yliopisto
Number of pages6
ISBN (Electronic)978-952-64-9656-6
Publication statusPublished - 2024
MoE publication typeA4 Conference publication
EventBaltic Mechatronics Symposium - Tallinn, Estonia
Duration: 3 May 20243 May 2024
Conference number: 9

Conference

ConferenceBaltic Mechatronics Symposium
Country/TerritoryEstonia
CityTallinn
Period03/05/202403/05/2024

Keywords

  • accelerometer
  • temperature measurement
  • GPS
  • wearable sensors
  • dog behaviour

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