CANINE COMPANION: Ensuring your Pet’s Safety and Health using IoT & ML

With the surge in global pet ownership, the demand for intelligent and responsive pet care systems has intensified. Conventional monitoring approaches, such as infrequent vet visits and isolated GPS collars, often fall short in providing proactive and comprehensive health insights. This research introduces an economical, IoT-driven pet wellness system integrating ESP32 microcontroller, biometric sensors, geolocation tracking, and machine learning intelligence. By continuously monitoring physiological parameters—heart rate, body temperature, and blood oxygen saturation—and pairing this with GPS tracking, the system ensures holistic care. Cloud-based data visualization through ThingSpeak and predictive analysis via supervised ML algorithms provide actionable insights. Alerts are transmitted to pet owners in real-time using Telegram integration, thereby enhancing emergency responsiveness. This study emphasizes the system's design, deployment, and operational viability for responsible and effective animal care.

Authors

Publication Details

Journal
International Journal of Innovative Research in Advanced Engineering
Published
2025-05-08
DOI
https://doi.org/10.26562/ijirae.2025.v1204.12
Primary Topic
Smart Systems and Machine Learning
Type
article
Field-Weighted Citation Impact
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article

CANINE COMPANION: Ensuring your Pet’s Safety and Health using IoT & ML

Anusha Parthiv
International Journal of Innovative Research in Advanced Engineering
Smart Systems and Machine Learning
article

CANINE COMPANION: Ensuring your Pet’s Safety and Health using IoT & ML

Anusha Parthiv
article en

Abstract

With the surge in global pet ownership, the demand for intelligent and responsive pet care systems has intensified. Conventional monitoring approaches, such as infrequent vet visits and isolated GPS collars, often fall short in providing proactive and comprehensive health insights. This research introduces an economical, IoT-driven pet wellness system integrating ESP32 microcontroller, biometric sensors, geolocation tracking, and machine learning intelligence. By continuously monitoring physiological parameters—heart rate, body temperature, and blood oxygen saturation—and pairing this with GPS tracking, the system ensures holistic care. Cloud-based data visualization through ThingSpeak and predictive analysis via supervised ML algorithms provide actionable insights. Alerts are transmitted to pet owners in real-time using Telegram integration, thereby enhancing emergency responsiveness. This study emphasizes the system's design, deployment, and operational viability for responsible and effective animal care.

International Journal of Innovative Research in Advanced EngineeringVol. 12(04)
Openalex Percentile: Top 90%
Smart Systems and Machine Learning
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