Report Title：Towards a Practical Crowdsensing System for Monitoring Road Surface Conditions

Time：December 1, 20179:00-10:00am

Address：61#4172

Contents of the Report:

Next generation intelligent transportation systems (ITS) of future road traffic monitoring are required to provide reports of traffic congestion, road conditions and surface anomalies, and driver behaviour.Road surface anomalies contribute to increased risk of traffic accidents, reduced driver comfort and increased wear of vehicles.The success of ITS relies on their ability to provide drivers with accurate real-time information. Robust crowdsensing for intelligent road services is becoming essential for future establishment of smart cities. This presentation discusses the development and demonstrates the performance of road surface anomalies monitoring based on motion sensors in land vehicles and smart devices. A framework for monitoring road surface anomalies is also introduced and discussed. Different vehicles were used in this research, spanning different sizes, and year model for extensive road experiments. These trajectories were used to collect and build multiple labeled data sets. In order to enhance the performance of the measurements, wavelet packet de-noising is used to enable efficient classification of road surface anomalies. We adopt statistical, time domain and frequency domain features to distinguish different road anomalies. The data sets collected are used to build, train, and test a system classifier through machine learning techniques to detect and categorize road anomalies. Furthermore, we analyze and assess the capabilities of the smart devices and other sensors to accurately geo-reference the road surface anomalies. Several road test experiments examining the benefits and assessing the performance of the proposed architecture are presented and discussed in this presentation.

Reporter：

Dr. AboelmagdNoureldin is a Professor at the Departments of Electrical and Computer Engineering, Royal Military College of Canada (RMCC) with Cross-Appointment at both the School of Computing and the Department of Electrical and Computer Engineering, Queen’s University. He is also the founder and the director of the Navigation and Instrumentation research group at RMCC. His research is related to GPS, wireless location and navigation, indoor positioning and multi-sensor fusion.

Dr. Noureldin holds B.Sc. degree in Electrical Engineering (1993) and M.Sc. degree in Engineering Physics (1997) from Cairo University, Egypt. In addition, he holds Ph.D. degree in Electrical and Computer Engineering (2002) from The University of Calgary, Alberta, Canada. Dr. Noureldin is a Senior member of IEEE.He has published more than 230 papers in journals and conference proceedings. Dr. Noureldin’s research work led to 10 patents in the area of position, location and navigation systems.

http://www.ece.queensu.ca/directory/crossappointed/noureldin.html