[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127961-en":3,"doc-seo-127961-105":31,"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":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},127961,687207024643,"Oliver","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","A Platform for Integrating Internet of Things, Machine Learning, and Big Data Practicum in Electrical Engineering Curricula - Research Report - 2024","Integration of the Internet of Things (IoT), big data, and machine learning (ML) is positioned as a driver of transformation across multiple fields, including electrical engineering education. The work introduces the IoT-Edu-ML-Stream open-source platform, implemented as GUI-based emulation software. It enables students to emulate connected IoT devices that stream correlated data via MQTT to a big data platform, then design and train ML models for decisionmaking. Learning outcomes are proposed and assessed via a comprehensive survey, showing improved IoT knowledge and practical skills as well as intuitive understanding of core ML analytics.","Zayed University  \nZU Scholars  \nAll Works  \n8-15-2024  \nA Platform for Integrating Internet of Things, Machine Learning, and Big Data Practicum in Electrical Engineering Curricula  \nNandana Jayachandran United Arab Emirates University  \nAtef Abdrabou  \nUnited Arab Emirates University  \nNaod Yamane  \nUnited Arab Emirates University  \nAnwer Al-Dulaimi Zayed University  \nFollow this and additional works at: [https://zuscholars.zu.ac.ae/works](https://zuscholars.zu.ac.ae/works)  \n Part of the Computer Sciences Commons  \nRecommended Citation  \nJayachandran, Nandana; Abdrabou, Atef; Yamane, Naod; and Al-Dulaimi, Anwer, \"A Platform for Integrating Internet of Things, Machine Learning, and Big Data Practicum in Electrical Engineering Curricula\" (2024) . All Works. 6840.  \n[https://zuscholars.zu.ac.ae/works/6840](https://zuscholars.zu.ac.ae/works/6840)  \nThis Article is brought to you for free and open access by ZU Scholars. It has been accepted for inclusion in All Works by an authorized administrator of ZU Scholars. For more information, please contact [scholars@zu.ac.ae](scholars@zu.ac.ae).  \ncomputers   \nArticle  \nA Platform for Integrating Internet of Things, Machine Learning, and Big Data Practicum in Electrical Engineering Curricula  \nNandana Jayachandran 1, Atef Abdrabou 1, *, Naod Yamane 1 and Anwer Al-Dulaimi 2  \nCitation: Jayachandran, N.;  \nAbdrabou, A.; Yamane, N.;  \nAl-Dulaimi, A. A Platform for Integrating Internet of Things, Machine Learning, and Big Data Practicum in Electrical Engineering Curricula. Computers 2024, 13, 198 . [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)computers13080198  \nAcademic Editor: Ananda Maiti  \nReceived: 3 July 2024  \nRevised: 9 August 2024  \nAccepted: 12 August 2024  \nPublished: 15 August 2024  \nCopyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \n1 Department of Electrical and Communication Engineering, College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates; [700046308@uaeu.ac.ae](700046308@uaeu.ac.ae) (N.J.); [201850217@uaeu.ac.ae](201850217@uaeu.ac.ae) (N.Y.)  \n2 College of Technical Innovations, Zayed University, Abu Dhabi P.O. Box 144534, United Arab Emirates; [anwer.al-dulaimi@zu.ac.ae](anwer.al-dulaimi@zu.ac.ae)  \n* Correspondence: [atef.abdrabou@uaeu.ac.ae](atef.abdrabou@uaeu.ac.ae); Tel.: +971-3-713-5149  \nAbstract: The integration of the Internet of Things (IoT), big data, and machine learning (ML) has pioneered a transformation across several fields. Equipping electrical engineering students to remain abreast of the dynamic technological landscape is vital. This underscores the necessity for an educational tool that can be integrated into electrical engineering curricula to offer a practical way of learning the concepts and the integration of IoT, big data, and ML. Thus, this paper offers the IoT-Edu-ML-Stream open-source platform, a graphical user interface (GUI)-based emulation software tool to help electrical engineering students design and emulate IoT-based use cases with big data analytics. The tool supports the emulation or the actual connectivity of a large number of IoT devices. The emulated devices can generate realistic correlated IoT data and stream it via the message queuing telemetry transport (MQTT) protocol to a big data platform. The tool allows students to design ML models with different algorithms for their chosen use cases and train them for decisionmaking based on the streamed data. Moreover, the paper proposes learning outcomes to be targeted when integrating the tool into an electrical engineering curriculum. The tool is evaluated using a comprehensive survey. The survey results show that the ","cbCairtT5NvW1fiw","https://ap.wps.com/l/cbCairtT5NvW1fiw","pdf",5828415,2,1,28,"English","en",105,"# Introduction\n## IoT in electrical engineering curricula\n## AI and autonomous intelligent systems\n# Platform overview\n## IoT-Edu-ML-Stream purpose and workflow\n## GUI emulation and MQTT streaming\n## ML model design and training\n# Evaluation and learning outcomes\n## Survey-based assessment results","[{\"question\":\"What platform is proposed for electrical engineering students in the curricula?\",\"answer\":\"The paper presents IoT-Edu-ML-Stream, a GUI-based open-source emulation platform to support practical learning of IoT, big data analytics, and machine learning in electrical engineering courses.\"},{\"question\":\"How does the platform generate and deliver IoT data to the big data component?\",\"answer\":\"Emulated IoT devices can generate realistic correlated IoT data and stream it via the MQTT protocol to a big data platform.\"},{\"question\":\"How was the platform evaluated and what were the main outcomes?\",\"answer\":\"A comprehensive survey was used to evaluate the tool. Results indicate students gained significant IoT knowledge and improved practical skills in designing real-world use cases, along with intuitive understanding of fundamental ML analytics.\"}]","A Platform for Integrating Internet of Things, Machine Learning, and Big Data Practicum in Electrical Engineering Curricula - Research Report - 2024 | PDF",1785943331,71,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"a-platform-for-integrating-internet-of-things-machine-learning-and-big-data-practicum-in-electrical-engineering-curricula-research-report-2024","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/a-platform-for-integrating-internet-of-things-machine-learning-and-big-data-practicum-in-electrical-engineering-curricula-research-report-2024/127961/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-27","2026-08-05",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 platform is proposed for electrical engineering students in the curricula?","Question",{"text":76,"@type":77},"The paper presents IoT-Edu-ML-Stream, a GUI-based open-source emulation platform to support practical learning of IoT, big data analytics, and machine learning in electrical engineering courses.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How does the platform generate and deliver IoT data to the big data component?",{"text":81,"@type":77},"Emulated IoT devices can generate realistic correlated IoT data and stream it via the MQTT protocol to a big data platform.",{"name":83,"@type":74,"acceptedAnswer":84},"How was the platform evaluated and what were the main outcomes?",{"text":85,"@type":77},"A comprehensive survey was used to evaluate the tool. 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