Saeed Mahmoud AL Shurafa
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Saeed Mahmoud AL Shurafa has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Firas Basim Ismail
Power Generation Unit, Institute of Power Engineering (IPE), Universiti Tenaga Nasional (UNITEN), Kajang 43000, Malaysia
2 shared publications - Ahmed Faeq Hussein
Department of Artificial Intelligence and Robotics Engineering, College of Engineering, Al- Nahrain University, Baghdad, Iraq
1 shared publication - Auns Qusai Al-Neami
Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Baghdad, IRAQ
1 shared publication - Ibrahim M. Albayati
School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, UK
1 shared publication - Mohammad A. AlMubaidin
Department of Civil Engineering, Aqaba University of Technology, Aqaba, Jordan
1 shared publication - R. H. Al-Hadeethi
School of Engineering and Digital Technologies, Faculty of Management, Sciences and Engineering, University of Bradford, Bradford, UK
1 shared publication
Latest Publications
- 5 September 2026
- Published by Springer Nature in Wireless Networks
- Vol. 32 (5) , 2903-2932
Artificial intelligence for power optimization in bluetooth low energy wearables: a narrative review
- 5 September 2026
- Published by Springer Nature in Wireless Networks
- Vol. 32 (5) , 2903-2932
Artificial intelligence for power optimization in bluetooth low energy wearables: a narrative review
- Open Access
- 31 August 2026
- Published by Springer Nature in International Journal of Energy and Water Resources
- Vol. 10 (3) , 120
Advancing energy efficiency in smart transportation through intelligent technologies and policy innovation
The transportation sector remains one of the largest contributors to global energy consumption and carbon emissions, particularly in rapidly urbanizing and emerging economies. This study presents an integrative review of intelligent technologies, system optimization approaches, and policy frameworks aimed at improving transportation energy efficiency, with a focused assessment of the Association of Southeast Asian Nations (ASEAN) member states. By synthesizing evidence from peer-reviewed literature, international energy databases, and official policy documents, the study evaluates the roles of transport electrification, intelligent transport systems, artificial intelligence–based energy management, and regulatory support mechanisms. The analysis reveals that electrification alone delivers limited efficiency gains unless integrated with artificial intelligence–driven optimization tools such as predictive analytics, real-time traffic management, and coordinated energy–transport system control. Evidence from Malaysia, Thailand, and Indonesia demonstrates notable progress in electric vehicle incentives, manufacturing strategies, and battery supply chain development, while highlighting persistent barriers including inadequate charging infrastructure, fragmented regulations, data limitations, and supply chain instability. The findings further emphasize that alternative fuels and system-level operational strategies remain essential complementary solutions. Unlike previous reviews that examine transport electrification, intelligent transport systems, artificial intelligence applications, or policy measures separately, this study develops an integrated analytical perspective that evaluates their combined influence on transportation energy efficiency. The principal contribution of the review is the development of a unified AI-enabled conceptual framework that positions artificial intelligence as the central coordinating layer linking vehicle technologies, transport operations, energy management systems, and policy instruments. By focusing on ASEAN economies while maintaining broader applicability to emerging regions, the framework provides strategic guidance for accelerating the transition toward intelligent, energy-efficient, and climate-resilient transportation systems.
- 31 August 2026
- Published by Springer Nature in International Journal of Energy and Water Resources
- Vol. 10 (3) , 120
Open AccessAdvancing energy efficiency in smart transportation through intelligent technologies and policy innovation
The transportation sector remains one of the largest contributors to global energy consumption and carbon emissions, particularly in rapidly urbanizing and emerging economies. This study presents an integrative review of intelligent technologies, system optimization approaches, and policy frameworks aimed at improving transportation energy efficiency, with a focused assessment of the Association of Southeast Asian Nations (ASEAN) member states. By synthesizing evidence from peer-reviewed literature, international energy databases, and official policy documents, the study evaluates the roles of transport electrification, intelligent transport systems, artificial intelligence–based energy management, and regulatory support mechanisms. The analysis reveals that electrification alone delivers limited efficiency gains unless integrated with artificial intelligence–driven optimization tools such as predictive analytics, real-time traffic management, and coordinated energy–transport system control. Evidence from Malaysia, Thailand, and Indonesia demonstrates notable progress in electric vehicle incentives, manufacturing strategies, and battery supply chain development, while highlighting persistent barriers including inadequate charging infrastructure, fragmented regulations, data limitations, and supply chain instability. The findings further emphasize that alternative fuels and system-level operational strategies remain essential complementary solutions. Unlike previous reviews that examine transport electrification, intelligent transport systems, artificial intelligence applications, or policy measures separately, this study develops an integrated analytical perspective that evaluates their combined influence on transportation energy efficiency. The principal contribution of the review is the development of a unified AI-enabled conceptual framework that positions artificial intelligence as the central coordinating layer linking vehicle technologies, transport operations, energy management systems, and policy instruments. By focusing on ASEAN economies while maintaining broader applicability to emerging regions, the framework provides strategic guidance for accelerating the transition toward intelligent, energy-efficient, and climate-resilient transportation systems.