[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124132-en":3,"doc-seo-124132-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124132,7971461740909,"Levi","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",6,"Technology","A Machine Learning Approach for Smart Waste Management Systems that is Automated","A waste management system supports disposing, reducing, reusing, and preventing waste, covering methods such as recycling, composting, incineration, landfills, and bioremediation. Traditional scheduling-based operations are inefficient and costly, while urban waste management demands substantial labor and impacts natural, budgetary, efficiency, and social dimensions. The work proposes an automated waste classification problem using machine learning and extends an AutoML-driven, data-driven process to improve accuracy and recall versus manually engineered models.","A Machine Learning Approach for Smart Waste Management Systems that is Automated  \nC. Rajkumar1 , K. Hari Prasath 2 , S. Hariharan 3  \n1 Assistant Professor, Department of Computer Applications, Dr. SNS Rajalakshmi College of Arts & Science, Coimbatore, Tamil Nadu, India  \n2, 3 PG Student, II MCA, Department of Computer Applications, Dr. SNS Rajalakshmi College of Arts & Science, Coimbatore, Tamil Nadu, India  \nAbstract: A waste management system is the concept in an organization that is used to dispose, reduce, reuse, and prevent waste. Some of the waste disposal methods are recycling, composting, incineration, landfills, bioremediation, waste of energy, and waste minimization. Traditional waste management system operates based on daily schedule which is highly inefficient and costly. Numerous data-driven methods for solving the problem are investigated in a realistic setting where most of the events are not actual emptying. Waste management is a daily task in urban areas, which requires a large amount of labour resources and affects natural, budgetary, efficiency, and social aspects. Many approaches have been proposed to optimize waste management, such as using the nearest neighbour search, colony optimization, genetic algorithm, and particle swarm optimization methods. The isolation of waste is done by unskilled workers which are less effective, time-consuming, and not plausible because of a lot of waste. So, proposing an automated waste classification problem utilizing Machine Learning algorithms. The use of machine learning allows  \nimproving the classification accuracy and recall of the existing manually engineered model. Keywords: Machine Learning, Waste Management, Automation, Classification, Smart System.  \n1. INTRODUCTION  \nThe waste management system predominantly corroborates the disposal and treatment of different types of waste. Thus, it safeguards human beings, animals, and surroundings [1] . Adequate waste management techniques can save much money, which will lead to improved air quality and less environmental pollution. Waste management requires necessary processes and activities to dominate from its inception to demolition. Waste comes in solid, liquid, or gaseous form, and every type of waste demands a different method of classification, disposal, and management. Waste management deals with every waste category, including household, organic, industrial, municipal, biomedical, organic, biological, and radioactive waste. Any unnecessary substance or substance with no use is called “waste”. Waste management involves the collection of the waste and its transport and disposal to appropriate locations. Machine learning is an area with a huge potential for the transformation of many areas of life and science including industrial informatics. In order to hasten the application of machine learning to real-world problems, the automated machine learning (AutoML) approach has been proposed. This article extends the AutoML approach with the datadriven methodology applied to industrial problems with existing (e.g. , model-based) solutions. The methodology includes five steps:  \n➢ Collection of data, which can be used during the development and evaluation of solutions;  \n➢ The collected data are used to evaluate the existing solution to the problem;  \n➢ Parameters of the existing solution are optimised and evaluated based on the data;  \n➢ Conventional machine learning algorithms can be applied to the problem;  \n➢ The feature engineering methods are used to find if additional features could improve the results of the machine learning algorithms.  \nThe methodology is applied to a problem within an area of waste management, which is one of the biggest challenges imposed by the rapid growth of the urban population. For example, in Europe each person is expected to yearly produce six tones of waste of materials used in the daily life. An efficient strategy for facing the challenge of the waste management should address several ","cbCait7ZJDqaRksq","https://ap.wps.com/l/cbCait7ZJDqaRksq","pdf",260495,1,7,"English","en",105,"# Introduction\n## AutoML-based data-driven methodology\n## Smart waste management with IoT and prediction\n## Sensor-based detection of container emptying","[{\"question\":\"Why are traditional waste management systems considered inefficient?\",\"answer\":\"They rely on fixed daily schedules, which increases cost and reduces efficiency. Labor-intensive handling and less effective waste isolation further weaken performance.\"},{\"question\":\"What is the proposed solution for waste classification?\",\"answer\":\"The document proposes an automated waste classification approach using machine learning, aiming to improve classification accuracy and recall compared with manually engineered models.\"},{\"question\":\"How does IoT improve smart waste management in this approach?\",\"answer\":\"IoT-enabled recycling containers can report filling levels, enabling prediction of the expected emptying time and helping avoid redundant transportation while preventing overfilling.\"}]","A Machine Learning Approach for Smart Waste Management Systems that is Automated | PDF",1785820628,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-machine-learning-approach-for-smart-waste-management-systems-that-is-automated","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/technology/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-machine-learning-approach-for-smart-waste-management-systems-that-is-automated/124132/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why are traditional waste management systems considered inefficient?","Question",{"text":75,"@type":76},"They rely on fixed daily schedules, which increases cost and reduces efficiency. Labor-intensive handling and less effective waste isolation further weaken performance.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is the proposed solution for waste classification?",{"text":80,"@type":76},"The document proposes an automated waste classification approach using machine learning, aiming to improve classification accuracy and recall compared with manually engineered models.",{"name":82,"@type":73,"acceptedAnswer":83},"How does IoT improve smart waste management in this approach?",{"text":84,"@type":76},"IoT-enabled recycling containers can report filling levels, enabling prediction of the expected emptying time and helping avoid redundant transportation while preventing overfilling.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,113,117,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":111,"slug":112},50,"technology",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":114,"show_sort_weight":115,"slug":116},"Healthcare",40,"healthcare",{"id":118,"doc_module":4,"doc_module_name":46,"category_name":119,"show_sort_weight":120,"slug":121},8,"Research & Report",30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]