A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics

Rahman, Md. Arafatur and Md. Abdur, Rahim and Rahman, Md Mustafizur and Moustafa, Nour and Imran, Razzak and Ahmad, Tanvir and Patwary, Mohammad N. (2022) A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics. IEEE Transactions on Intelligent Transportation Systems. pp. 1-16. ISSN 1524-9050. (Published)

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Abstract

The dependency on vehicles is increasing tremendously due to its excellent transport capacity, fast, efficient, flexible, pleasant journey, minimal physical effort, and substantial economic impact. As a result, the demand for smart and intelligent feature enhancement is growing and becoming a prime concern for maximum productivity based on the current perspective. In this case, the Internet of Everything (IoE) is an emerging concept that can play an essential role in the automotive industry by integrating the stakeholders, process, data, and things via networked connections. But the unavailability of intelligent features leads to negligence about proper maintenance of vehicle vulnerable parts, reckless driving and severe accident, lack of instructive driving, and improper decision, which incurred extra expenses for maintenance besides hindering national economic growth. For this, we proposed a conceptual framework for a central VHMS exploiting IoE-driven Multi-Layer Heterogeneous Networks (HetNet) and a machine learning technique to oversee individual vehicle health conditions, notify the respective owner-driver real-timely and store the information for further necessary action. This article transparently portrayed an overview of central VHMS and proposed the taxonomy to achieve such an objective. Subsequently, we unveiled the framework for central VHMS, IoE-driven Multi-tire HetNet, with a secure and trustworthy data collection and analytics system. Finally, anticipating this proposition's outcome is immense in the automotive sector. It may motivate the researcher to develop a central intelligent and secure vehicular condition diagnostic system to move this sector towards Industry 4.0.

Item Type:	Article
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Central VHMS; Communication system security; Fourth Industrial Revolution; HetNet; IoE; machine learning; Monitoring; Optical fiber networks; Stakeholders; Taxonomy; VehiChain.; Wireless sensor networks
Subjects:	Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery
Faculty/Division:	Faculty of Mechanical Engineering Institute of Postgraduate Studies College of Engineering Faculty of Computing
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	04 Jul 2022 09:07
Last Modified:	04 Jul 2022 09:07
URI:	http://umpir.ump.edu.my/id/eprint/33360
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