[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124494-en":3,"doc-seo-124494-105":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},124494,13056703020460,"Valentina","https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923",8,"Research & Report","Machine Learning and Device’s Neighborhood-Enabled Fusion Algorithm for the Internet of Things","Internet of Things environments rely on information fusion to refine data from densely deployed consumer electronic devices before edge processing. Existing methods focus on raw-data tuning but overlook the neighborhood context of nearby devices. A machine learning and neighborhood-assisted fusion approach is proposed where servers accept device invitations within coverage areas, use K-mean and SVM to refine captured values, and exploit redundancy among proximate devices. Simulations evaluate lifetime, energy efficiency, and refinement ratio, reaching about a 30% fusion-ratio improvement.","Machine Learning and Device’s Neighborhood-Enabled Fusion Algorithm for the Internet of Things  \nAmal Al-Rasheed, Tahani Alsaedi, Rahim Khan, Bharati Rathore, Gaurav Dhiman ,  \nMahwish Kundi, and Aftab Ahmad  \nAbstract—In the Internet of Things, information fusion is among the crucial problems and probably occurs due to the dense deployment of consumer electronic devices. In the literature, various methodologies have been developed to fine-tune raw data; however, consumer electronic devices’ neighborhood information has been completely ignored. In this manuscript, a machine learning and neighborhood-assisted fusion approach has been developed for consumer electronic devices to ensure that captured data values have been properly refined before onward processing at the respective edge. In this approach, every server accepts member request invitations from electronic devices deployed in its coverage area. It applies the well-known K-mean and supports vector machine (SVM) algorithms to refine captured data values by consumer electronic devices. Apart from that, the server module has the built-in intelligence to compare the captured data values of those electronic devices, which reside nearby and probably have a higher redundancy ratio. Simulation results have concluded that the proposed machine learningassisted fusion approach is an ideal solution for the IoT in general and the Artificial Intelligent-enabled IoT in particular. Additionally, the proposed algorithm was thoroughly examined via various performance evaluation metrics such as lifetime, energy efficiency, and refinement ratio, where it has shown convincing results such as 30% improvement in the fusion ratio.  \nIndex Terms—Internet of Things, machine learning, K-mean, information fusion, outliers.  \nI. INTRODUCTION  \nTHE DEVELOPMENT of a smart and intelligent auto  \nmated communication infrastructure across different  \nReceived 25 June 2024; revised 6 October 2024; accepted 13 November 2024. Date of publication 24 February 2025; date of current version 12 June 2025 . This work was supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia, under Project PNURSP2024R235 . (Corresponding author: Rahim Khan.)  \nAmal Al-Rasheed is with the Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia.  \nTahani Alsaedi is with the Applied College, Taibah University, Madinah 42353, Saudi Arabia.  \nRahim Khan and Aftab Ahmad are with the Computer Science Department, Abdul Wali Khan University Mardan, Mardan 25000, Pakistan (e-mail: [rahimkhan@awkum.edu.pk](rahimkhan@awkum.edu.pk)).  \nBharati Rathore is with the School of Business and Creative Industries, University of South Wales, CF37 1DL Pontypridd, U.K.  \nGaurav Dhiman is with the Department of Computer Science and Engineering, Yuan Ze University, Tao Yuan, Taiwan, and also with the Centre of Research Impact and Outcome, Chitkara University, Rajpura 140417, Punjab, India.  \nMahwish Kundi is with the Maynooth International Engineering College, Maynooth University, Maynooth, W23 F2H6 Ireland.  \nDigital Object Identifier 10.1109/TCE.2024.3500024  \napplication areas is subjected to the careful integration of both artificial intelligence and Internet of Things. In the IoT, modules or devices are deployed, either randomly or manually, in the closed proximity of the underlined phenomenon, that is required to be monitored, and capture crucial information after a defined time intervals [1], [2] . Additionally, every module is required to transmit its captured data via a shared communication channel to the respective server module in the IoT [3], [4] . These devices could become more smarter if artificial intelligence-enabled techniques have been incorporated along with the traditional programming modules. Moreover, artificial intelligence-enabled modules have","cbCaicLJMrSXgZWA","https://ap.wps.com/l/cbCaicLJMrSXgZWA","pdf",942299,1,9,"English","en",105,"# Abstract and Index Terms\n# Introduction","[{\"question\":\"Why is information fusion important in the Internet of Things?\",\"answer\":\"Information fusion is crucial because IoT devices capture raw data that must be properly refined before further processing at the edge. Dense deployments increase the likelihood of redundancy and outliers, making fusion essential.\"},{\"question\":\"How does the proposed fusion approach use neighborhood information?\",\"answer\":\"Servers collect invitation requests from electronic devices in their coverage area, then compare captured values from nearby devices that likely share higher redundancy. This neighborhood context helps refine the data more effectively.\"},{\"question\":\"Which algorithms are used to refine captured data values?\",\"answer\":\"The approach applies K-mean and supports vector machine (SVM) to refine captured data values before downstream processing.\"}]","Machine Learning and Device’s Neighborhood-Enabled Fusion Algorithm for the Internet of Things | PDF",1785822761,23,{"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},"machine-learning-and-devices-neighborhood-enabled-fusion-algorithm-for-the-internet-of-things","",{"@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/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-and-devices-neighborhood-enabled-fusion-algorithm-for-the-internet-of-things/124494/",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 is information fusion important in the Internet of Things?","Question",{"text":75,"@type":76},"Information fusion is crucial because IoT devices capture raw data that must be properly refined before further processing at the edge. Dense deployments increase the likelihood of redundancy and outliers, making fusion essential.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the proposed fusion approach use neighborhood information?",{"text":80,"@type":76},"Servers collect invitation requests from electronic devices in their coverage area, then compare captured values from nearby devices that likely share higher redundancy. This neighborhood context helps refine the data more effectively.",{"name":82,"@type":73,"acceptedAnswer":83},"Which algorithms are used to refine captured data values?",{"text":84,"@type":76},"The approach applies K-mean and supports vector machine (SVM) to refine captured data values before downstream processing.","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},[93,97,101,105,110,115,120,123,127,130,134],{"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":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},"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"]