MUMBAI, India, Aug. 24 -- Intellectual Property India has published a patent application (202641096396 A) filed by Rajalakshmi Engineering College on August 10, 2026, for A Sensor-Fusion-Driven Ai System For Autonomous Health And Behavior Intelligence In Livestock Farming.
Inventors include Dr. P. Kumar; and Vignesh C.
The application for the patent was published on August 21, 2026, under issue no. 34/2026.
Abstract: The present invention relates to an AI-based solution for sustainable livestock farming that enables early disease diagnosis and continuous behavioral monitoring through integrated sensing, embedded processing, and intelligent analytics. The invention addresses technical challenges associated with manual livestock health monitoring, delayed disease detection, and inefficient farm management practices. The system comprises wearable animal sensors configured to capture physiological and behavioral parameters including body temperature, movement intensity, posture, feeding activity, and rest patterns. Environmental sensors are deployed within livestock enclosures to monitor ambient temperature, humidity, air quality, and ammonia concentration, which directly influence animal health. Imaging devices, such as visible-light or infrared cameras, are positioned to capture visual indicators including gait abnormalities, lameness, and posture deviations. Data acquired from the sensors and imaging devices is processed by an embedded processing unit, which performs signal conditioning, noise filtering, synchronization, and feature extraction in real time. The extracted features are analyzed by an AI-based analytics engine employing trained machine learning or deep learning models to identify disease indicators, stress patterns, and abnormal behavior by comparing real-time data with learned baseline health profiles. Upon detection of health anomalies or behavioral deviations, the system generates alerts and diagnostic indicators, which are transmitted through an IoT communication module to remote monitoring dashboards or farm management platforms. This enables timely veterinary intervention, isolation of affected animals, and optimization of farm operations. The inventive contribution lies in the functional integration of physical sensing hardware, embedded real-time processing, and AI-driven analytics to provide autonomous livestock health assessment. The invention is not directed to a computer program per se but delivers a technical solution to the technical problem of real-time disease diagnosis and behavioral monitoring. The system produces a technical effect by improving diagnostic accuracy, reducing manual observation, and supporting sustainable livestock farming practices.
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