Intelligent Poultry Farm Management System Using Machine Learning

Abstract

This paper presents an integrated intelligent poultry farm management system that leverages IoT hardware, cloud computing, and machine learning to monitor environmental conditions and automate farm operations. Low-cost sensors (MQ137, BME280, load cells, ultrasonic) and an Arduino microcontroller collect real-time data on gas levels, temperature, humidity, feed, and water. This data is transmitted via GSM to an AWS-hosted backend (Node.js/Express,MongoDB) and made available through a React Native mobileapp with secure JWT authentication. Machine learning models for anomaly detection, classification, and regression analyze trends and predict conditions, enabling proactive interventions. The proposed architecture improves upon prior work by incorporating predictive analytics and a full-stack cloud–mobile solution with payment integration, enhancing poultry health, welfare, and farm productivity.