{"title":"Design of a Smart IoT-AI Enabled Recycling Machine with Gamification Techniques","authors":"Zineddine N. Haitaamar, Abdelrahman Shata","doi":"10.1109/MTTW56973.2022.9942465","DOIUrl":null,"url":null,"abstract":"Recycling is a crucial process in decreasing pollution and waste materials. Unfortunately, many people find it a time-consuming task and are not incentivized enough to do it, thus the need for a system to simplify the process and make it more enjoyable. The system uses a Convolutional Neural Network to detect and classify the waste material and then a hardware mechanism to segregate the waste. The model utilizes a custom dataset and achieves a precision of 89%. The system is also equipped with a sensor network which connects to the Internet and views the results on an Internet-of-Things platform.","PeriodicalId":426797,"journal":{"name":"2022 Workshop on Microwave Theory and Techniques in Wireless Communications (MTTW)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Workshop on Microwave Theory and Techniques in Wireless Communications (MTTW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MTTW56973.2022.9942465","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Recycling is a crucial process in decreasing pollution and waste materials. Unfortunately, many people find it a time-consuming task and are not incentivized enough to do it, thus the need for a system to simplify the process and make it more enjoyable. The system uses a Convolutional Neural Network to detect and classify the waste material and then a hardware mechanism to segregate the waste. The model utilizes a custom dataset and achieves a precision of 89%. The system is also equipped with a sensor network which connects to the Internet and views the results on an Internet-of-Things platform.