Advanced Smart Systems for Detecting and Mitigating Aggression in Poultry Farms Using CNN and SVM algorithm

Aggressive behavior in chickens can harm both animal welfare and farm output. Traditional techniques of detecting such behavior are mainly reliant on manual observation , which is inefficient and subject to human mistake. This paper describes a smart system that uses Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) algorithms to automatically detect and minimize aggressive behavior in chickens. Sensors and video surveillance were utilized to collect behavioral data, which was then extracted using the CNN model and classified using the SVM. This hybrid technique improves the system’s accuracy in spotting aggression, provides real-time insights, and allows for quick response. The proposed real-time insights, and allows for quick response. The proposed system aims to optimize animal welfare and improve overall farm management, providing an automated, accurate, and scalable solution for poultry welfare monitoring.