[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123086-en":3,"doc-seo-123086-105":30,"detail-sidebar-cat-0-en-105":92},{"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":20,"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},123086,1099514068035,"Ezra","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",6,"Technology","Quality-of-Things Based Machine Learning for the MIoT Applications","Enhancing the Quality of Things (QoT) is essential as the Multimedia Internet of Things (MIoT) evolves rapidly, where achieving Acceptable QoT (AQoT) becomes a core constraint. Meeting AQoT supports optimization of bandwidth and storage while satisfying the minimal requirements of MIoT applications. The study develops an MIoT system using machine learning to maintain minimum resource needs for high performance. Gaussian-Naive Bayes, Fine KNN, and AdaBoost are evaluated across video sequences under varied bitrates and network conditions. Face-recognition results for a Ring Video Doorbell scenario show machine learning can reach AQoT and reduce bandwidth and storage usage.","School of Engineering, Computing and Mathematics Faculty of Science and Engineering  \n2023-01-01  \nQuality-of-Things Based Machine Learning for the MIoT Applications  \nShaymaa Al-Juboori School of Engineering, Computing and Mathematics Ali H. Husseen Al-Nuaimi  \nAmulya Karaadi  \nIs Haka Mkwawa  \nJianwu Zhang Hangzhou Dianzi University et al. See next page for additional authors  \nLet us know how access to this document benefits you  \nGeneral rights  \nAll content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author. Take down policy  \nIf you believe that this document breaches copyright please contact the library providing details, and we will remove access to the work immediately and investigate your claim.  \nFollow this and additional works at: [https://pearl.plymouth.ac.uk/secam-research](https://pearl.plymouth.ac.uk/secam-research)  \nRecommended Citation  \nAl-Juboori, S., Al-Nuaimi, A., Karaadi, A., Mkwawa, I., Zhang, J., & Sun, L. (2023) 'Quality-of-Things Based Machine Learning for the MIoT Applications', Available at: 10. 1109/ICASSPW59220 .2023.10192929 This Conference Proceeding is brought to you for free and open access by the Faculty of Science and Engineering at PEARL. It has been accepted for inclusion in School of Engineering, Computing and Mathematics by an authorized administrator of PEARL. For more information, [please contact openresearch@plymouth.ac.uk](please contact openresearch@plymouth.ac.uk).  \nAuthors  \nShaymaa Al-Juboori, Ali H. Husseen Al-Nuaimi, Amulya Karaadi, Is Haka Mkwawa, Jianwu Zhang, and Lingfen Sun  \nThis conference proceeding is available at PEARL: [https://pearl.plymouth.ac.uk/secam-research/2010](https://pearl.plymouth.ac.uk/secam-research/2010)  \nPEARL  \nQuality-of-Things Based Machine Learning for the MIoT Applications  \nAl-Juboori, Shaymaa; Al-Nuaimi, Ali H. Husseen; Karaadi, Amulya; Mkwawa, Is Haka; Zhang, Jianwu ; Sun, Lingfen  \nDOI:  \n10.1109/ICASSPW59220.2023.10192929  \nPublication date:  \n2023  \nDocument version:  \nPublisher's PDF, also known as Version of record  \nLink:  \nLink to publication in PEARL  \nCitation for published version (APA):  \nAl-Juboori, S. , Al-Nuaimi, A. H. H. , Karaadi, A. , Mkwawa, I. H. , Zhang, J. , & Sun, L. (2023) . Quality-of-Things Based Machine Learning for the MIoT Applications. Paper presented at 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Greek island of Rhodes. [https://doi.org/10.1109/ICASSPW59220.2023.10192929](https://doi.org/10.1109/ICASSPW59220.2023.10192929)  \nAll content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Wherever possible please cite the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content  \nshould be sought from the publisher or author.  \nDownload date: 10. Apr. 2025  \nQUALITY-OF-THINGS BASED MACHINE LEARNING FOR THE MIOT APPLICATIONS  \nShaymaa Al-Juboori 1∗, AHAlnuaimi 1, Amulya Karaadi 1, Is-Haka Mkwawa 1, Jianwu Zhang2, Lingfen Sun 1  \n1 School of Engineering, Computing and Mathematics, University of Plymouth  \nPlymouth, PL4 8AA, United Kingdom  \n2 School of Communication Engineering, Hangzhou Dianzi University, Hangzhou 310018, PR China  \n∗ [shaymaa.al-juboori@plymouth.ac.uk](shaymaa.al-juboori@plymouth.ac.uk) , [L.Sun@plymouth.ac.uk](L.Sun@plymouth.ac.uk)  \nABSTRACT  \nEnhancing the Quality of Things (QoT) is urgently needed given the rapid evolution of the Multimedia Internet of Things (MIoT) . One of the challenges with MIoT is Acceptable QoT. Achieving AQoT can optimise bandwidth and storage at a","cbCait3Ac6YAEHwk","https://ap.wps.com/l/cbCait3Ac6YAEHwk","pdf",1793239,1,8,"English","en",105,"# Abstract\n# Introduction\n## Background: IoT and MIoT\n## Quality metrics: QoE and QoT\n# Method and evaluation\n## Machine learning algorithms\n## Video sequences and varying network conditions\n# Results\n## Ring Video Doorbell face recognition scenario\n## Bandwidth and storage reduction","[{\"question\":\"What problem does the document address in MIoT applications?\",\"answer\":\"It targets the challenge of achieving Acceptable Quality of Things (AQoT) in MIoT, which affects how bandwidth and storage can be optimized while meeting minimal application requirements.\"},{\"question\":\"How is machine learning used in the proposed MIoT system?\",\"answer\":\"Machine learning techniques are used to keep resource usage at minimum levels needed to maintain AQoT, while still achieving high performance in MIoT applications.\"},{\"question\":\"Which machine learning algorithms and evaluation scenario are reported?\",\"answer\":\"Gaussian-Naive Bayes, Fine KNN, and AdaBoost are tested on video sequences with varying bitrates and network conditions, and results are demonstrated using a Ring Video Doorbell face-recognition scenario.\"}]","Quality-of-Things Based Machine Learning for the MIoT Applications | PDF",1785814566,20,{"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":87,"head_meta":89,"extra_data":91,"updated_unix":28},"quality-of-things-based-machine-learning-for-the-miot-applications","",{"@graph":36,"@context":86},[37,54,69],{"@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/quality-of-things-based-machine-learning-for-the-miot-applications/123086/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05","2026-08-04",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What problem does the document address in MIoT applications?","Question",{"text":76,"@type":77},"It targets the challenge of achieving Acceptable Quality of Things (AQoT) in MIoT, which affects how bandwidth and storage can be optimized while meeting minimal application requirements.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How is machine learning used in the proposed MIoT system?",{"text":81,"@type":77},"Machine learning techniques are used to keep resource usage at minimum levels needed to maintain AQoT, while still achieving high performance in MIoT applications.",{"name":83,"@type":74,"acceptedAnswer":84},"Which machine learning algorithms and evaluation scenario are reported?",{"text":85,"@type":77},"Gaussian-Naive Bayes, Fine KNN, and AdaBoost are tested on video sequences with varying bitrates and network conditions, and results are demonstrated using a Ring Video Doorbell face-recognition scenario.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,114,119,123,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":112,"slug":113},50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":120,"show_sort_weight":121,"slug":122},"Research & Report",30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":29,"slug":126},9,"Religion & Spirituality","religion-spirituality",{"id":29,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":29,"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":107,"slug":137},19,"General","general"]