Automated Dairy Farm Management System Using Raspberry Pi, IoT and Machine Learning

Pooja 1, Dr.Vinita Patil 2, Dr.Basavalinga Swamy 3 , Prof .Sadhana C 4  , Dr. Sharanbasappa Shetkar 5

1Pooja Dept of VLSI Design and Embedded system, M.Tech student, LAEC, Bidar

2Dr.Vinita Patil, Professor, Department of ECE, LAEC Bidar

3Dr.Basavalinga Swamy, Associate Professor, Department of ECE, LAEC Bidar

4 Prof .Sadhana C, Assistant Professor, Department of ECE, LAEC Bidar

5Dr.Sharanbasappa Shetkar, Professor, Department of ECE, LAEC Bidar

Abstract – The dairy industry is increasingly adopting intelligent technologies to improve livestock management, enhance productivity, and reduce manual intervention. This paper presents an Automated Dairy Farm Management System based on Raspberry Pi 4, the Internet of Things (IoT), and Machine Learning (ML) for real-time monitoring and automation of dairy farm operations. The proposed system integrates multiple sensors to continuously monitor environmental parameters such as temperature, humidity, air quality, methane gas concentration, rainfall, and fire hazards. The collected data is processed by the Raspberry Pi and transmitted to a cloud platform, enabling farmers to remotely monitor farm conditions through a web-based dashboard. In addition to environmental monitoring, the system incorporates automated feeding, waste management, lighting control, and roof operation to improve operational efficiency and animal welfare. RFID and GPS modules are employed for cattle identification, location tracking, and geo-fencing to enhance livestock security. A Convolutional Neural Network (CNN)-based machine learning model is utilized to analyze cattle images and identify common diseases at an early stage, enabling timely veterinary intervention. The proposed approach combines sensing, automation, cloud computing, and artificial intelligence into a unified platform that supports precision livestock farming. The system offers a cost-effective, scalable, and energy-efficient solution suitable for small and medium-sized dairy farms. Experimental evaluation demonstrates that the proposed framework improves farm management efficiency, minimizes labor requirements, supports early disease detection, and enhances overall livestock health and productivity.

KeyWords: Raspberry Pi 4, Internet of Things (IoT), Smart Dairy Farming, Machine Learning, Convolutional Neural Network (CNN), Precision Livestock Farming, Cattle Disease Detection, RFID, GPS Tracking, Farm Automation, Environmental Monitoring, Cloud Computing..