Intelligent garbage classifying method based on machine learning

Abstract

The invention discloses an intelligent garbage classifying method based on machine learning. The intelligent garbage classifying method based on machine learning comprises the following steps that anautomatic garbage classifying system is provided and comprises a garbage sorting device, a plurality of garbage collecting devices, a plurality of sensors and a computer; a plurality of garbage categories to be divided are preset on the computer, garbage data corresponding to the garbage categories is input, and based on the input garbage data, a machine learning model is used for establishing corresponding garbage characteristics of the various garbage categories; according to the multiple garbage categories given by the computer in a default manner, a user selects the needed garbage category; materials to be classified are put into the garbage sorting device, the sensors collect the data of the materials, and the computer carries out characteristic extraction on the collected data, compares the extracted material characteristics with the garbage characteristics in the model and automatically distinguishes garbage category division results of the materials and the result credibility;and according to the garbage category division results of the materials, the garbage sorting device automatically sorts the materials to the corresponding garbage collecting devices.

Description

technical field [0001] The invention belongs to the technical field of garbage classification, in particular to a method for intelligent garbage classification based on machine learning. Background technique [0002] With China's economic development and urbanization process, more and more garbage is produced by residents; nearly two-thirds of China's cities are surrounded by garbage belts, and improper garbage disposal will cause a series of serious hazards . At present, in order to improve the living environment, some cities have successively issued a series of domestic waste classification management policies. For example, Xiamen City classifies domestic waste into four categories: recyclables, kitchen waste, hazardous waste, and other waste. Garbage is sorted to improve treatment efficiency in downstream waste treatment plants. At present, garbage sorting is mainly carried out manually by the sorting personnel. The sorting personnel need to make their own judgments on ...

AI Technical Summary

Problems solved by technology

At present, garbage sorting is mainly carried out manually by the sorting personnel. The sorting personnel need to make judgments on the classification of garbage and send it to the corresponding garbage bin. According to statistics, the sorting personnel make an average of 40 sorting operations per minute. Picking action has the disadvantages of high work intensity, low work efficiency and high misclassification rate after long-term work

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