Chicken Health Detection System using Edge Impulse with ESP32-Cam

Abstract

The integration of technology in the agricultural industry has led to significant advancements in efficiency, productivity, and animal welfare. Efficiency, output, and animal welfare have all significantly improved as a result of technology's incorporation into agriculture. Poultry farming, particularly chicken rearing, is a critical sector that generates demand for improved detection systems to ensure chicken wellbeing. The Chicken Health Detection System, created using Edge Impulse and ESP32-Cam, is a groundbreaking project that aims to transform poultry health detection and management. This system uses image analysis to track the health of chickens in real time using IoT technologies and machine learning techniques. The system can differentiate between healthy and unhealthy chickens by integrating Edge Impulse and ESP32-Cam, providing poultry farmers significant details. The system's capacity to provide timely insights into the welfare of chickens demonstrates its potential to revolutionize current monitoring approaches, hence encouraging enhanced welfare standards and increased production within the poultry industry. The development and deployment of the Chicken Health Detection System represent significant accomplishments in the endeavor to modernize chicken farming operations. It showcases the ability of technology to address challenging agricultural problems and sets a foundation for future innovations in this domain. The system will gain value from strategic recommendations for enhancement, including expanding the dataset, enhancing hardware components, and exploring innovative methods for machine learning.