Aarati Medehal, Aniruddha Annaluru, Shalini Bandyopadhyay, T. Chandar
{"title":"Automated Smart Garbage Monitoring System with Optimal Route Generation for Collection","authors":"Aarati Medehal, Aniruddha Annaluru, Shalini Bandyopadhyay, T. Chandar","doi":"10.1109/ISC251055.2020.9239002","DOIUrl":null,"url":null,"abstract":"One of the major concerns of the environment that strongly impacts the health and well-being of society is the detection, monitoring, and management of solid wastes. Slowly the world is stepping towards smart systems enabling complete automation of societies. The concept of smart cities, which is heavily based on Internet of Things (IoT) systems makes human lives more comfortable and secure in every aspect. As a result, smart waste management systems form an essential part of the establishment of smart cities. The conventional method of manually monitoring the wastes in waste bins is a tedious process and uses a lot of human effort, time, and cost which can easily be avoided with the current innovations. The garbage collection process is also highly redundant, inefficient, and can be vastly improved using Machine Learning (ML) algorithms. The purpose of this paper is to use the powerful tools of IoT to completely automate the process of garbage monitoring using ultrasonic sensors and NodeMCU and provide an optimal route for garbage collection using the cluster first-route second ML algorithm.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"19 12","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Smart Cities Conference (ISC2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISC251055.2020.9239002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
One of the major concerns of the environment that strongly impacts the health and well-being of society is the detection, monitoring, and management of solid wastes. Slowly the world is stepping towards smart systems enabling complete automation of societies. The concept of smart cities, which is heavily based on Internet of Things (IoT) systems makes human lives more comfortable and secure in every aspect. As a result, smart waste management systems form an essential part of the establishment of smart cities. The conventional method of manually monitoring the wastes in waste bins is a tedious process and uses a lot of human effort, time, and cost which can easily be avoided with the current innovations. The garbage collection process is also highly redundant, inefficient, and can be vastly improved using Machine Learning (ML) algorithms. The purpose of this paper is to use the powerful tools of IoT to completely automate the process of garbage monitoring using ultrasonic sensors and NodeMCU and provide an optimal route for garbage collection using the cluster first-route second ML algorithm.