Automated recognition of foodstuff placed into refrigerator

A low-cost system for automated recognition of foodstuff placed into the refrigerator is presented. Recognition is based on an alternation of temperature signal in the refrigerator interior. The nearest-neighbour classification by using a self-recognizing neural network is applied. The recognition rate of foodstuff is around 72%.