A Deep Learning and IoT based Food Quality Detection

Since it is the foundation of social development, solidness, and human well-being, food quality, and safety are the potential challenges. Since food is the underpinning aspect of human well-being, social advancement, and dependability, it is a critical challenge for society. Food processing at all stages from development, collection, and capacity to readiness and utilization should be considered to guarantee food quality and well-being. Be that as it may, these techniques habitually require more work. The progression of machine vision can help scientists extensively in food processing. The Internet of Things and machine learning technologies play significant role in determining the food quality. Support vector machines, neural networks, deep learning and low-cost cold storage based on IoT were applied to get over the challenges of tracking food quality and quantity. UV sensors, a wireless sensor for food quality detection by UHF RFID passive tags, and a radio frequency-powered sensor have all been utilized for monitoring the food quality. This paper discusses about different Machine Learning (ML) and IoT-based techniques and present CNN based food quality detection model based on the fruit dataset and finally the results were discussed.