IoT-Based Predictive Service for Early Disease Detection in Poultry Chickens

Poultry farming plays a vital role in meeting the rising global demand for high-quality protein. This paper presents an Internet of Things (IoT)-based system designed to monitor and safeguard poultry chickens from illness by tracking key environmental parameters such as temperature, humidity, air quality, lighting, and weight. The system employs a NodeMCU-ESP32 microcontroller with built-in Wi-Fi, integrated with DHT11 (temperature and humidity sensor), MQ135 (gas detector), load cell (for weight), and LDR (light sensor). Automated responses, such as activating cooling and exhaust fans with buzzer alerts, are triggered when conditions exceed set thresholds, and real-time notifications are sent to farmers via a mobile app. Beyond monitoring, the system incorporates predictive analytics using machine learning algorithms to identify patterns and correlations in collected data, enabling early disease detection. This proactive approach allows for timely intervention, significantly reducing mortality rates and economic losses while improving overall poultry health and productivity.