Development of an IoT-Based System with AI-Driven Robotic Feeder and Rice Hull Management for Chickens

This research developed an IoT-based system that integrates an AI-driven robotic feeder and rice hull management to improve sustainability of poultry farming. The system continuously monitors environmental conditions - humidity, temperature, and ammonia levels-, automating the feeding process through behavior detection by YOLOv8 model and dispensing rice hulls based on ammonia thresholds. Using sensors, actuators, and a user-friendly web interface, the system provides real-time data to minimize manual labor, and enhance waste management. The setup includes an ammonia sensor, temperature and humidity sensors, an AI-driven robotic feeder aided by YOLOv8 algorithm, an automated rice hull dispenser, a microprocessor for data processing, and a cloud platform for data storage and accessibility. The results show that the system effectively maintains environmental conditions and automates feeding, improving farm productivity. The system's remote monitoring capabilities, with AI-driven automation enhance poultry farms' operations. By merging IoT technology with AI, the system addresses key challenges in poultry farming, demonstrating a sustainable approach that can adapt to both small and large-scale operations.