IOT-DRIVEN HEALTH MONITORING SYSTEMS FOR BROILER AND NOILER CHICKENS: A SMART PRECISION FARMING APPROACH

Abstract

he poultry industry is essential for global food security, with broiler and Noiler chickens being major contributors to meat production. Traditional poultry farming relies on manual monitoring, which is labor-intensive and inefficient. The Internet of Things (IoT) offers a transformative approach by enabling real-time health monitoring, automation, and data-driven decision-making in poultry management. This study evaluates the impact of an IoT-driven health monitoring system on broiler and Noiler chickens' health, growth, and productivity. A total of 100 chickens are divided into two groups: an experimental group housed in IoT-equipped units with automated monitoring and a control group managed using traditional methods. IoT sensors continuously measure critical parameters such as temperature, humidity, ammonia levels, feed intake, and movement. Real-time data analysis enables early detection of diseases, stress, and abnormal behavior, while the control group relies on manual observation. Preliminary results suggest that IoT-driven monitoring improves poultry health by ensuring timely interventions, reducing mortality, and enhancing feed conversion efficiency. Automated environmental controls minimize stress and maximize weight gain. The study also examines the economic benefits of IoT adoption in commercial poultry farms, emphasizing improved productivity and cost savings. This research highlights the potential of IoT-based health monitoring to revolutionize poultry farming, making it more efficient and sustainable. Future studies will integrate artificial intelligence (AI) for predictive analytics to enhance poultry health management and productivity.