Machine vision-based design of human-machine interactive waste bins for shopping mall areas

With the rapid development of cities, the output of domestic garbage per capita has also increased. In response to the national policy call, it aims to solve the garbage classification problem in the public areas of shopping malls. In this paper, intelligent garbage disposal equipment for large shopping malls is designed by using automatic control technology and a convolution neural network algorithm. Starting from the structural design, the equipment has built modules such as feeding induction, storage compression, disinfection and sterilization, overflow detection, etc. On this basis, the intelligent garbage classification is realized by combining the convolution neural network algorithm. At the same time, automatic control technology is introduced to create an automatic control system, which creates a unique human-computer interaction experience. The device provides convenient garbage sorting treatment and a good human-computer interaction experience for mall visitors, reduces the work intensity of subsequent manual sorting, and promotes the implementation of a garbage sorting policy.