Freshness of Food Detection Using Iot and Machine Learning

In today's world, food spoilage is a crucial problem as consuming spoiled food is harmful for consumers. Our proposed work aims at detecting spoiled food using appropriate sensors and monitoring gases like carbon monoxide, ammonia and benzene which are released by the particular food item. A micro controller named Arduino that senses this and issues an alert using internet of things, so that appropriate action can be taken. This approach has widespread applications in the food industry, where manual detection methods are prevalent. The preservation of food freshness is critical for ensuring consumer safety and reducing wastage. The proposed machine learning algorithm, Support Vector Machine, has been integrated into this model to estimate the likelihood of food spoilage when purchased from a specific vendor. This will increase competition among retailers to sell more healthy and fresh food and create a safe world for all consumers alike. Through this approach, our project not only enhances food safety but also promotes a culture of freshness and quality in the food supply chain.