Hossain, Md Naeem and Rahim, Md. Abdur and Rahman, Md Mustafizur and D., Ramasamy (2025) Artificial intelligence revolutionising the automotive sector: A comprehensive review of current insights, challenges, and future scope. Computers, Materials and Continua, 82 (3). pp. 3643-3692. ISSN 1546-2218. (Published)
![[img]](http://umpir.ump.edu.my/style/images/fileicons/other.png) |
Pdf
Artificial intelligence revolutionising the automotive sector.pdf Restricted to Repository staff only Available under License Creative Commons Attribution. Download (2MB) | Request a copy |
|
|
Pdf
Artificial intelligence revolutionising the automotive sector.pdf - Published Version Available under License Creative Commons Attribution. Download (2MB) | Preview |
Abstract
The automotive sector is crucial in modern society, facilitating essential transportation needs across personal, commercial, and logistical domains while significantly contributing to national economic development and employment generation. The transformative impact of Artificial Intelligence (AI) has revolutionised multiple facets of the automotive industry, encompassing intelligent manufacturing processes, diagnostic systems, control mechanisms, supply chain operations, customer service platforms, and traffic management solutions. While extensive research exists on the above aspects of AI applications in automotive contexts, there is a compelling need to synthesise this knowledge comprehensively to guide and inspire future research. This review introduces a novel taxonomic framework that provides a holistic perspective on AI integration into the automotive sector, focusing on next-generation AI methods and their critical implementation aspects. Additionally, the proposed conceptual framework for real-time condition monitoring of electric vehicle subsystems delivers actionable maintenance recommendations to stakeholders, addressing a critical gap in the field. The review highlights that AI has significantly expedited the development of autonomous vehicles regarding navigation, decision-making, and safety features through the use of advanced algorithms and deep learning structures. Furthermore, it identifies advanced driver assistance systems, vehicle health monitoring, and predictive maintenance as the most impactful AI applications, transforming operational safety and maintenance efficiency in modern automotive technologies. The work is beneficial to understanding the various use cases of AI in the different automotive domains, where AI maintains a state-of-the-art for sector-specific applications, providing a strong foundation for meeting Industry 4.0 needs and encouraging AI use among more nascent industry segments. The current work is intended to consolidate previous works while shedding some light on future research directions in promoting further growth of AI-based innovations in the scope of automotive applications.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Artificial intelligence; AI techniques; automotive sector; autonomous vehicle; decision-making; VHMS |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Faculty/Division: | Institute of Postgraduate Studies Centre of Excellence: Automotive Engineering Centre Centre of Excellence: Automotive Engineering Centre Faculty of Mechanical and Automotive Engineering Technology |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 24 Feb 2025 03:07 |
| Last Modified: | 07 Mar 2025 07:46 |
| URI: | http://umpir.ump.edu.my/id/eprint/43894 |
| Download Statistic: | View Download Statistics |
Actions (login required)
 |
View Item |