Intelligent garbage can and garbage classification method based on deep learning

Abstract

The invention provides an intelligent garbage can and a garbage classification method based on deep learning. The intelligent garbage can comprises a garbage can body and a plurality of classificationgarbage boxes arranged in the garbage can body, the garbage can further comprises a control device, a metal detection device, a garbage image acquisition device and a classification garbage box doorcontrol device, wherein the metal detection device is used for collecting the metal attributes of garbage to be classified in real time, the garbage image acquisition device is used for collecting image information of the garbage to be classified in real time, the classification garbage box door control device is connected with the control device and is used for controlling box door switches of the classification garbage boxes, and the control device is used for driving the classification garbage box door control device to act according to the metal attributes of the garbage to be classified and the image information of the garbage to be classified, so that the garbage to be classified falls into the corresponding classification garbage boxes. The intelligent garbage can has the advantagesof being scientific in design, high in practicability, convenient to classify, capable of saving energy and low in production cost.

Description

technical field [0001] The invention relates to the technical field of garbage sorting, in particular to an intelligent trash can and a garbage sorting method based on deep learning. Background technique [0002] The recycling rate of waste glass in life is as high as 90% in Europe, while in my country 85% is mixed with garbage and discarded. The utilization rate of renewable resources in my country is low, especially low-value recyclables such as waste glass, waste textiles, and waste packaging paper are discarded in large quantities, which not only intensifies the trend of garbage siege, but also causes environmental pollution. [0003] The reporter learned from research that there are multiple constraints in the field of renewable resources in my country, such as disordered recycling system, lack of product standards, and backward technology. The proportion of foreign steel scrap in raw materials exceeds that of iron ore. The utilization rate of scrap steel in developed ...

AI Technical Summary

Problems solved by technology

[0007] Disadvantages: It requires the thinking of the garbage thrower to distinguish the categories of garbage in hand. If there is no understanding of the general classification of garbage materials and garbage types, there is a high possibility of misjudgment of the recyclable nature of garbage, so that the garbage cannot be returned correctly. into the corresponding box; it needs to be inspected by the staff in the later stage, and it cannot be completely classified

[0010] Defects: Compared with the traditional trash cans that are only classified by markings on the box body, this type of trash can still does not give the answer to the garbage classification problem of the trash can itself. In other words, its essence is still a manual classification that requires human operation , only expanded and optimized the structure of the trash can and other uses, and the production cost of the trash can is also very high

[0012] Disadvantages: relatively high cost, complex design structure, relatively poor stability due to strong linkage between machines, difficult to popularize and develop, and consumes a lot of energy

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