Livestock Monitoring and Management System
S Manasa, Swetha S Manasa, Raghavendra Tuller, S Ritish, Prashant P Walikar, Gagan
Abstract: This paper presents an IoT-based livestock monitoring and management system designed to improve animal health, productivity, and agricultural sustainability. Key parameters like temperature are recorded by IoT sensors on livestock that send information about their location, movement, and grazing patterns to a central platform wirelessly. The system enables real-time tracking, geo-fencing, herd safety, and early disease detection, reducing operational inefficiencies and supporting timely interventions. Machine learning algorithms further analyze the collected data to detect irregularities, predict health risks, and enhance breeding and feeding practices. Examination of historical data aids in resource allocation and emission monitoring, which supports sustainable livestock practices. By integrating IoT with intelligent analytics, the proposed system transforms conventional livestock management into a smart, automated, and data-driven approach, enhancing animal welfare and ensuring long-term agricultural sustainability.