A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics
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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers Inc.
2022
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| Online Access: | http://umpir.ump.edu.my/id/eprint/33360/1/A%20secure%20and%20intelligent%20framework%20for%20vehicle%20health%20monitoring%20exploiting%20big-data%20analytics.pdf |
| _version_ | 1796994955156127744 |
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| author | Rahman, Md. Arafatur Md. Abdur, Rahim Rahman, Md Mustafizur Moustafa, Nour Imran, Razzak Ahmad, Tanvir Patwary, Mohammad N. |
| author_facet | Rahman, Md. Arafatur Md. Abdur, Rahim Rahman, Md Mustafizur Moustafa, Nour Imran, Razzak Ahmad, Tanvir Patwary, Mohammad N. |
| author_sort | Rahman, Md. Arafatur |
| collection | UMP |
| description | 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. |
| first_indexed | 2024-03-06T12:55:12Z |
| format | Article |
| id | UMPir33360 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:55:12Z |
| publishDate | 2022 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | UMPir333602022-07-04T09:07:38Z http://umpir.ump.edu.my/id/eprint/33360/ A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics Rahman, Md. Arafatur Md. Abdur, Rahim Rahman, Md Mustafizur Moustafa, Nour Imran, Razzak Ahmad, Tanvir Patwary, Mohammad N. QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery 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. Institute of Electrical and Electronics Engineers Inc. 2022 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/33360/1/A%20secure%20and%20intelligent%20framework%20for%20vehicle%20health%20monitoring%20exploiting%20big-data%20analytics.pdf 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) https://doi.org/10.1109/TITS.2021.3138255 https://doi.org/10.1109/TITS.2021.3138255 |
| spellingShingle | QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery Rahman, Md. Arafatur Md. Abdur, Rahim Rahman, Md Mustafizur Moustafa, Nour Imran, Razzak Ahmad, Tanvir Patwary, Mohammad N. A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics |
| title | A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics |
| title_full | A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics |
| title_fullStr | A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics |
| title_full_unstemmed | A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics |
| title_short | A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics |
| title_sort | secure and intelligent framework for vehicle health monitoring exploiting big data analytics |
| topic | QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/33360/1/A%20secure%20and%20intelligent%20framework%20for%20vehicle%20health%20monitoring%20exploiting%20big-data%20analytics.pdf |
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