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A Deep Learning Approach to Smart Refrigerator System with the assistance of IOT

Smart refrigerator refers to refrigerators that are capable of taking decisions without human interactions. It takes decision with the help of sensors as perception medium and software as the logical decision maker. The main challenge set for this work was to make it cost efficient so that anyone can own this smart refrigerator. As a result this work focuses on developing a smart refrigerator which uses minimum amount of sensors to perceive its surroundings and maximum efficiency from software to make up for the lack of sensors and intelligent decision making. Also this work uses convolutional neural network architecture and transfer learning technique, Inception V3 pre-trained model to detect the items present in the refrigerator and make a decision. It shows faster precision performance with less consumption of other resources. This work mainly focuses on developing a theoretical model of proposed refrigerator which will automate our daily refrigerator activity with a small demonstration of the proposed model with developing a CNN model that can detect food. This paper describes the work process in detail followed by found result and future improvements.