[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119846-en":3,"doc-seo-119846-105":30,"detail-sidebar-cat-0-en-105":90},{"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},119846,16904993612988,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Exploring Machine Learning in IoT Smart Home Automation - Research Overview","The Internet of Things (IoT) has expanded rapidly across industries and research areas, enabling smart applications such as smart cities, infrastructure, healthcare, and agriculture. Smart homes use remote and automated control to improve daily life, but effective operation requires machine learning (ML) beyond basic automation. This research classifies smart home automation applications and proposes an ML taxonomy based on application type, supported by surveys, literature reviews, open challenges, issues, and future research directions.","TITLE:\nExploring Machine Learning in IoT Smart Home Automation\nAuthor:\nQuadri Waseem, Wan Isni Sofiah Wan Din*, Azamuddin Bin Ab Rahman, Kashif Nisar\nCorresponding Author: sofiah@ump.edu.my\nFaculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah, Kuantan, Pahang, Malaysia. Professional Computing & Data, Science, Swinburne University of Technology, New South Wales, Australia.\nAbstract:\nThe Internet of Things (IoT) has evolved in these years. Various types of organizations, industries, research domains and almost all types of intelligent future applications are utilizing the advantages of IoT. These applications include smart homes, smart cities, smart infrastructure smart communities, smart healthcare, smart agriculture and many more. \"Smart Homes” has emerged as one the latest Internet of Things (IoT) applications known to automate household equipment’s using remote or automated functioning from remote locations to improve the quality of life for its inhabitants. For a smart home system to function effectively, the machine learning (ML) implementation must go beyond basic remote control and simple automation. To fully realize its potential and provide homeowners with tremendous and unexpected benefits, more research and development in the fields of machine intelligence and smart home automation are required. In this research work, we aim to traverse ML in IoT smart home automation by classifying the home automation applications. We propose a taxonomy of machine learning (ML) for smart homes based on its application. This research also includes related surveys and literature reviews along with open challenges and issues as well as future directions in detail.\nKeywords:\nMachine Learning, Smart Home, Automation, Applications\nACKNOWLEDGMENT\nThis research was fully funded by the UMP Research Grant Scheme under grant RDU220374 and Tabung Persidangan Dalam Negara (TPDN), UMP\nREFERENCES\n[1] Forootan, Mohammad Mahdi, et al. \"Machine learning and deep learning in energy systems: A review.\" Sustainability 14.8 (2022): 4832.\n[2] Zaidan, A. A., and B. B. Zaidan. \"A review on intelligent process for smart home applications based on IoT: coherent taxonomy, motivation, open challenges, and recommendations.\" Artificial Intelligence Review 53.1 (2020): 141-165.\n[3] Jaihar, John, et al. \"Smart home automation using machine learning algorithms.\" 2020 International Conference for Emerging Technology (INCET). IEEE, 2020.\n[4] Haria, Harsh, and Bilal N. Shaikh Mohammad. \"Home Automation System Using IoT and Machine Learning Techniques.\" Proceedings of the 3rd International Conference on Advances in Science & Technology (ICAST). 2020.","cbCaibZdXarB5fdL","https://ap.wps.com/l/cbCaibZdXarB5fdL","docx",15884,1,2,"English","en",105,"# Smart Home Automation and IoT Context\n## Need for Machine Learning in Smart Homes\n# Proposed ML Taxonomy for Smart Homes\n## Classification of Smart Home Applications\n# Related Surveys and Literature Review\n## Open Challenges, Issues, and Future Directions","[{\"question\":\"Why does smart home automation require machine learning beyond basic remote control?\",\"answer\":\"A smart home system must move past simple automation to fully realize its potential and deliver meaningful benefits. ML provides smarter intelligence for effective operation.\"},{\"question\":\"What is the main contribution of this research on ML for IoT smart homes?\",\"answer\":\"The work classifies home automation applications and proposes an ML taxonomy for smart homes based on application type.\"},{\"question\":\"What additional materials are included besides the proposed taxonomy?\",\"answer\":\"The research includes related surveys and literature reviews, along with open challenges and issues and detailed future directions.\"}]","Exploring Machine Learning in IoT Smart Home Automation - Research Overview | DOCX",1785726633,5,{"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":85,"head_meta":87,"extra_data":89,"updated_unix":28},"exploring-machine-learning-in-iot-smart-home-automation-research-overview","",{"@graph":36,"@context":84},[37,53,67],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,47,50],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":21},"https://docshare.wps.com/document/","Document",{"item":48,"name":12,"@type":43,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/exploring-machine-learning-in-iot-smart-home-automation-research-overview/119846/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/vnd.openxmlformats-officedocument.wordprocessingml.document","2026-08-03",true,{"@type":64,"interactionType":65,"userInteractionCount":20},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"Why does smart home automation require machine learning beyond basic remote control?","Question",{"text":74,"@type":75},"A smart home system must move past simple automation to fully realize its potential and deliver meaningful benefits. 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