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Fakultät für Elektrotechnik und Informationstechnik
Persons standing with two drones in front of them © TU Dortmund

First Prize, IEEE ComSoc Student Competition Winners, 2018, Supervisor: Fang-Jing Wu

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Image of the award certificate © CNI

The outcome of our students’ project group has been awarded the First Prize by IEEE ComSoc Member and Global Activities Council for the IEEE ComSoc Student Competition 2018 in Abu Dhabi, United Arab Emirates. The project group entitled “Passenger Flows: Crowd Mobility Analytics with Edge Computing in Public Transport” is supervised by Junior Professor Dr. Fang-Jing Wu at the Department of Electrical Engineering and Information Technology, Communication Networks Institute, TU Dortmund. The student team formed by Lucas Döring, Stephanie Althoff, Kai Bitterschulte, Keng Yip Chai, Damian Grabarczyk, Yunfeng Huang, and Lidong Mao, exploits Internet-of-Things techniques combined with machine learning algorithms to solve one of the important issues in public transport in smart cities. The goal of the developed system is to monitor passenger flows in an automated public transport system. To achieve this goal, lightweight embedded devices are integrated with multiple types of sensors for sensing wireless network activities and environmental conditions, and the onboard passenger estimation algorithms are designed for analyzing real-time data and further visualization. Therefore, the technical issues in wireless opportunistic communications, multi-modal sensing and data analytics, and visualization are addressed by the team. To conduct real-world experiments, the designed prototype was validated in the H-Bahn Dortmund that is an automated hanging train in the TU Dortmund’s campus.

The developed system was evaluated by an international committee with 45 experts nominated by the Competition Co-Chairs and by IEEE ComSoc Technical Committee, covering all areas. Two-round evaluation processes were performed by the committee from different aspects of social impact, technical content, originality, practical applicability and results, and quality of presentation. The developed system is characterized by giving insight into the uncertain wireless traffic and environmental conditions via an integration of sensing techniques, statistical learning algorithms, prototyping, and practical experiments in the real world, which makes the work particularly compelling and provide a physical gateway to a connected cyber world. Congratulations to the team at Communication Networks Institute, TU Dortmund.

More details can be found on the IEEE ComSoc website in the Student Competition Winners section.

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