@article{ZHU2023, 
author = {Chen ZHU and Xichen ZHANG and Senjie LI and Zhiguo SHI and Shibo HE},
title = {Design of intelligent waste sorting system based on cloud edge collaboration},
year = {2023},
journal = {Experimental Technology and Management},
volume = {40},
number = {9},
pages = {74-80,186},
keywords = {cloud platform, cloud-edge collaboration, data enhancement, waste sorting},
url = {https://www.sciopen.com/article/10.16791/j.cnki.sjg.2023.09.011},
doi = {10.16791/j.cnki.sjg.2023.09.011},
abstract = {In order to meet the intelligent demand of waste sorting and the centralized management of classification equipment, an intelligent waste sorting system based on cloud edge collaboration was designed and developed. The system uses Raspberry Pi and Alibaba Cloud HaaS100 development board as the edge end master equipment, and Alibaba Cloud IOT platform as the cloud platform. The system selects 245 categories of waste sorting dataset provided by Baidu PaddlePaddle, and combines data enhancement and cloud edge collaboration technology to train, test and deploy three lightweight waste sorting algorithms. The experimental results show that data augmentation can improve the Top-1 accuracy of the algorithm model on the test set by about 1%, and cloud edge collaboration can achieve a Top-1 accuracy of 98.80% for Raspberry Pi in inference, which can meet practical usage needs.}
}