IoT for Road Safety: Innovations, Challenges, and Future Directions
Track ID: Spes-12
The advancement of the Internet of Things (IoT) technology has opened up new possibilities for improving road safety. By connecting vehicles, infrastructure, and various sensors, IoT enables real-time data collection, analysis, and communication to enhance road safety measures. This special session aims to explore the innovative applications, challenges, and potential of IoT in ensuring safer roads and reducing accidents.
Topics of Interest
We invite researchers, practitioners, and experts to share their knowledge, experiences, and insights related to IoT applications in road safety. Potential topics of interest include, but are not limited to:
- Intelligent transportation systems for road safety using IoT
- IoT-enabled vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication
- Real-time monitoring and analysis of road conditions and traffic flow
- IoT-based driver assistance systems and collision avoidance technologies
- Smart infrastructure for road safety, including smart traffic lights and signage
- Data analytics and machine learning for predictive maintenance and accident prevention
- Cybersecurity and privacy considerations in IoT-enabled road safety systems
- Integration of IoT with emerging technologies like AI, blockchain, and edge computing for road safety
- Case studies and success stories of IoT implementation in road safety
- Ethical and societal implications of IoT-enabled road safety solutions
Please note that submissions are not limited to the listed topics, and we encourage innovative contributions that push the boundaries of IoT in road safety.
Paper Submission Deadline
- Deadline for Paper Submissions: July 30th, 2023
- Acceptance Notification: September 8th, 2023
- Deadline for Camera-Ready Paper Submissions: September 18th, 2023
- Deadline for Presentation Submissions: October 2nd, 2023
Papers should be six (6) pages in length and follow the instruction provided for the main Conference. The conference allows up to two additional pages for a maximum length of eight (8) pages with payment of extra page charges once the paper has been accepted.
Please submit your paper for this Special Session using the link to eWorks:
Call For Papers:
If you have any questions, please contact Dr. Abd-Elhamid M. Taha: firstname.lastname@example.org
Abd-Elhamid Taha: Alfaisal University
Abd-Elhamid M. Taha is the Director of Research and Innovation at Alfaisal University and an Associate Professor in electrical engineering. He holds an adjunct post at the School of Computing at Queen's. His research centers on computer networks and communications, particularly the integration of IoT, affective sensing, and AI. He serves as an Area Editor for the Canadian Journal of Electrical and Computer Engineering and Associate Editor for the IEEE Communications Magazine. Additionally, he chairs the Communications Software Technical Committee within the IEEE Communications Society.
Sharief Oteafy: DePaul University
Dr. Oteafy, a PhD recipient from Queen's University, specializes in adaptive resource management in Next Generation Sensing Networks. As the IEEE ComSoc Ad Hoc and Sensor Networks (AHSN) Standards Liaison, he actively contributes to IEEE and ACM. His achievements include the Howard Staveley Teaching Award and nominations for teaching excellence. With publications, workshops, and a book to his credit, Dr. Oteafy's research focuses on next-gen networking, IoT, Tactile Internet, Big Sensed Data management, contextual awareness in the Internet of Skills, and Information Centric Networks. He serves as an Associate Editor for IEEE Access and on Wiley's editorial board.
Mohamed Abusharkh: Ferrist State University
Dr. Mohamed Abusharkh is an assistant professor and program coordinator for Digital Media Software Engineering at Ferris State University. With a PhD from Western University, his research focuses on resource management in Next Generation Cloud computing. He combines industry experience as a software implementation consultant with research expertise in modeling, optimization, and performance evaluation. His projects include resource allocation, Cloud systems performance, high availability, energy efficiency, and machine learning, collaborating with partners like Samsung and Ericsson. Current research interests encompass Cloud computing resource optimization, natural language processing, real-time bidding for Cloud resources in IoT environments, machine learning, and autonomous vehicles.