Intelligent Machine for Food Quality and Safety Assessment - Vinayak K.; Anagha M; Kiran T.R; Thara K.V; Binesh Mohan P (International Journal of Industrial and Product Design Engineering, 2024)
This paper presents the development of an intelligent fruit and vegetable classification system aimed at reducing food waste and infections caused by spoiled items. Using artificial intelligence and sensor data, our system classifies items into three categories: ripe, unripe, and rotten, and employs servo motors to sort them into respective baskets. The classification process utilizes real-time temperature, humidity, and image data captured by the camera and processed by the laptop. Additionally, the nutritional information of the ripen fruits are provided after classification. The system employs DC motors for conveyor belt movement, IR proximity sensors for item detection, and DHT11 sensors for environmental monitoring and are controlled by an Arduino Uno R3 microcontroller. Our work demonstrates the potential of such a system in reducing food waste, aiding in diet control, and assisting farmers in agricultural sorting tasks. Overall, this research contributes to the development of intelligent systems for efficient food management, benefiting both consumers and agricultural stakeholders.
Keywords: DC motors; Diet control; Food management; Nutritional information; artificial intelligence