基于机器学习的智能垃圾分类系统设计

近几十年人们对于垃圾分类处理越来越重视，针对目前人工垃圾分类工作量大，效率较低等问题，提出了基于机器学用ＢＲＩＳＫ特征提取算法，实现图像检测，以ＪＱ８４００语音模块实现语音播报功能。经测试，本系统进行垃圾分类的准确度达到习的智能垃圾分类系统。以ＳＴＭ３２Ｆ１０３ＺＥＴ６单片机作为主控模块，以ＯｐｅｎＭｖ４Ｈ７作为摄像头采集模块，采集垃圾图片，采９８％，可以按照目前的垃圾分类方案播报为厨余垃圾、有害垃圾、其他垃圾、可回收垃圾。系统操作简单，性能可靠，成本低，完成了垃圾识别与检测功能

Design of an Intelligent Garbage Classification System Based on MachineLearning

In recent decades, people pay more and more attention to garbage disposal. Aiming at the problems of heavy workload and low efficiency of manual garbage classification, an intelligent garbage classification system based on machine learning is proposed. This design uses STM32F103ZET6 as the main control module and OpenMv4 H7 as the camera acquisition module to collect garbage pictures. BRISK feature extraction algorithm is adopted to realize image detection, and JQ8400 voice module is used to realize voice broadcast function. After testing, the correctness of the system''s garbage classification reaches 98%, which can be categorized as kitchen waste, harmful waste, other waste and recyclable waste according to the current garbage classification scheme. The system is simple in operation, reliable in performance and low in cost.