Smart Poultry Farming: CNN-Driven Environmental Optimization for Sustainability

The Internet of Things (IoT) has revolutionized the poultry farming industry by enabling real-time monitoring and optimization of environmental parameters crucial for bird health and productivity. However, traditional algorithms such as Support Vector Machines (SVMs), Fuzzy logic are limited by high computational costs, inefficiency with large datasets, and vulnerability to overfitting in noisy data. To overcome these challenges, a novel IoT-based framework has been developed, integrating Convolutional Neural Networks (CNNs) with IoT sensors to monitor and optimize temperature, humidity, and air quality in poultry farms. It excels in learning from data, handling non-linear relationships, adapting to changing conditions, and controlling multiple parameters in real-time, making accurate predictions and adjustments through pattern recognition and precise modeling. This system leverages advanced image processing and deep learning techniques to provide real-time data analysis and predictive maintenance, ensuring optimal conditions for poultry health and productivity. By harnessing the power of IoT and CNNs, this innovative approach enables conscientious and efficient farming practices, tailored to meet the intensified demands of the global poultry market.