Leveraging AI and IoT for Smart Transportation in the UAE: Challenges, Opportunities, and Strategic Roadmap
The United Arab Emirates strengthens its position as a transport leader through AI and IoT integration as tools to enhance mobility. Researchers assess AI and IoT implementation at four primary transportation points: smart traffic logistics systems and intelligent public transport networks and autonomous vehicles together with multimodal transportation platforms. The Autonomous Emergency Braking system (AEB) stands out as a vital feature which uses artificial intelligence to detect potential collisions promptly followed by automatic braking for preventing accidents in real-time. The technology has not reached its maximum capability because of limitations in technology and regulations alongside public worries about reliability and safety. Public acceptance of AVs remains slower because multiple incidents have shown doubts about their reliability despite their safety and efficiency benefits. The research proposes an essential partnership method for government entities to unite with private firms and academic institutions to build a dependable system of transportation technology that provides peak efficiency and innovation. The development of AV systems and associated technology such as AEB depends on technological advancement and the implementation of regulations and public awareness initiatives to build trust with users. The UAE's establishment of an environment fostering research cooperation between government and manufacturers and regulatory support will create effective environmental transportation solutions which will establish international standards.
Authors
- Ved Prakash Mishra (ORCID: https://orcid.org/0000-0003-1832-8736)
- Akshay Kumar (ORCID: https://orcid.org/0000-0002-3684-8498)
- Parampreet Kaur (ORCID: https://orcid.org/0000-0002-2491-9615)
- Akash Badhan
Institutions
- Lovely Professional University (IN)
- Amity University (AE)
Publication Details
- Published
- 2025-04-24
- DOI
- https://doi.org/10.1109/icoei65986.2025.11013108
- Citations
- 2
- Primary Topic
- Organizational and Employee Performance
- Type
- article
- Field-Weighted Citation Impact
- 4.96