MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641074372 A) filed by Mohan Kandasamy; Sri Shanmugha College Of Engineering And Technology; Udhaya S; Kaviyatharshini V; Mohana Shree M S; Sowndhararajan M; Dharmaraj V; Pramoth Kumar S; and Harini A on June 16, 2026, for Smart Livestock Health Monitoring System.
Inventors include Mohan Kandasamy; Sri Shanmugha College Of Engineering And Technology; Udhaya S; Kaviyatharshini V; Mohana Shree M S; Sowndhararajan M; Dharmaraj V; Pramoth Kumar S; and Harini A.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: The present invention relates to a Smart Livestock Health Monitoring System that enables continuous and automated real-time monitoring of the physiological health parameters of farm animals using Internet of Things (IoT) technology. The system comprises an ESP32 microcontroller integrated with a DS18B20 temperature sensor, MAX30102 pulse oximeter sensor for heart rate and SpO2 measurement, and an MPU6050 accelerometer sensor for activity and movement detection. The collected sensor data is transmitted wirelessly via Wi-Fi to a FastAPIbased backend server, where it is validated, processed, and stored in a structured database. The system employs predefined threshold-based health classification logic to identify normal, warning, and critical conditions in livestock. Upon detection of abnormal physiological conditions, the system triggers a dual-channel alert notification mechanism that simultaneously delivers SMS alerts to farmers and veterinary doctors through a GSM module (SIM800L) and push notifications through the Blynk IoT mobile application. A web-based dashboard developed using HTML, CSS, and JavaScript provides real-time data visualization of sensor readings and health status. The system achieves a sensor accuracy of 97–100% for temperature, heart rate, and motion detection parameters. The invention provides a cost-effective, scalable, and fault-tolerant solution suitable for deployment in rural and semi-urban livestock farming environments, improving animal welfare, enabling early disease detection, and reducing manual monitoring effort.
Disclaimer: Curated by HT Syndication.
