IoT Based Meat Freshness Classification Using Deep Learning

This paper presents an innovative Internet of Things (IoT) system that integrates gas sensors and a custom Convolutional Neural Network (CNN) to classify the freshness and species of beef and mutton in real time. The CNN, trained on 9,928 images, achieved 99% accuracy, outperforming models like ResNet-50, SVM, and KNN. The system uses three gas sensors (MQ135, MQ4, MQ136) to detect gases such as ammonia, methane, and hydrogen sulfide, which indicate meat spoilage. Real-time feedback is provided via LED indicators (green for fresh, yellow for partially fresh, red for rotten), with results displayed on an LED screen. This IoT system offers an efficient and reliable solution for real-time meat quality monitoring.