Food wastage Analysis Framework using Comprehensive IoT-Based Multi-Sensor

Wasting of food is a key issue in most parts of the world, which is associated with losing food nutrition, health risks, and the environment. Ineffectiveness of the currently used detection means is an indication that there is need to have intelligent and real-time monitoring mechanisms. In this work, an IoT-based multi-sensor system incorporating NDIR CO 2, DHT 22, and MQ-4 sensors to detect and predict the presence of important environmental indicators (carbon dioxide, temperature, humidity, and methane concentration) will be proposed to monitor food spoilage. The cloud-based machine learning methods are used to process sensor data to classify the freshness state of food products. Prediction was confirmed by experimental validation of the system on different fruits, vegetables, and foodstuff with an overall accuracy of 95% supporting the reliability of the system. The introduced framework provides a scalable and effectual solution for reducing food waste, enhancing food safety, and improving supply chain sustainability.