A Smart IOT-Based Cattle Health Monitoring System with Machine Learning Integration
Abstract— Efficient livestock health monitoring is essential for improving productivity and reducing losses caused by diseases. This paper presents an IoT-based cattle health monitoring system integrated with machine learning to predict cattle health status and identify potential diseases. By leveraging real-time sensor data, Firebase cloud storage, predictive models, and a web-based interface for health visualization, the system enables precise, data-driven interventions. Key diseases addressed include Bovine Respiratory Disease (BRD), Mastitis, Heat Stress, Foot and Mouth Disease (FMD), Ketosis and Lameness. The system's user-friendly design provides medical insights, making it a valuable tool for farmers and veterinarians. Keywords—IoT cattle health monitoring, machine learning in livestock, disease prediction, Bovine Respiratory Disease (BRD), Mastitis, Heat Stress, Foot and Mouth Disease (FMD), Ketosis, Lameness, real-time monitoring, Firebase, livestock management, cattle health visualization, veterinary decision support, smart farming solutions.
Authors
- Mr. GOWTHAM TJ
Publication Details
- Journal
- INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
- Published
- 2025-05-06
- DOI
- https://doi.org/10.55041/ijsrem46936
- Primary Topic
- Food Supply Chain Traceability
- Type
- article
- Field-Weighted Citation Impact
- 0.00