Food Spoilage Detection Powered By IoT & Ml

Food spoilage is among the major issues against public health and environmental sustainability and leads to a loss in addition to the more significant waste of resources. Therefore, a novel food spoilage detection and monitoring system has been proposed with the integration of IoT technology and ML to enhance food safety and reduce waste. The smart system will be using a network of sensors to monitor continuous environment variables like temperature, humidity, and gas emissions within the storage facilities. Data streams from these sensors can be further analyzed through advanced algorithms with ML like Random Forest Classifier to detect spoilage patterns and predict the shelf life remaining for the perishable items. It integrates a user-friendly interface that enables customers to receive real-time alerts and actionable insights, which can be used by stakeholders to intervene accordingly in time. Therefore, with the integration of IoT and ML, this solution ensures freshness in food products and promotes sustainability through a decrease in food and resource waste. Through several scenarios, the results presented prove that this system can be effectively implemented, thereby making a system like ours more alluring and feasible for larger deployments in the food supply chain.