In today's world, food spoilage is a crucial problem as consuming spoiled food is harmful for consumers. Excess food waste is something that regularly occurs at hotels, family functions, parties, etc. To gain an understanding of the scale of the problem, the excess food we waste has a large impact on various environmental factors. Freshness is a significant indicator of the quality of seafood and other food products. Food processing, storage, and marketing of food and edible products all heavily rely on the rapid detection of their freshness. We have developed an Object Detection Algorithm YOLO model that can predict the freshness of the food samples with image and its smell in a more accurate level with less time. We also take the level of gas emitted by rotten food samples using sensors and detect the spoilage level using the IoT. We can determine the affected or rotten areas by combining the value from both image data and gas emitted by the given food sample. The result can be viewed in an application through a browser. Hence, this model achieves better results interms of accuracy, precision and recall.