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Title	A Proof Of Concept For Providing Traffic Data By Ai Based Computer Vision As A Basis For Smarter Industrial Areas
ID_Doc	3836
Authors	Shams A.; Schekelmann A.; Mülder W.
Year	2022
Published	Procedia Computer Science, 201, C
DOI	http://dx.doi.org/10.1016/j.procs.2022.03.033
Abstract	Algorithms and data serve as the foundation for any SMART approach, whether smart cities or smart urban environments. Availability of near real-time data for such smart applications in a wider geographic area is an expensive undertaking on both the technical and financial front. We introduce an approach to reduce technical and financial barriers to enable near real-time data collection. Additionally, our approach can be scaled with no significant technical depth. Our proposed approach was applied to meet the challenge of underutilized collaboration and data in a semi-closed harbor situated near Neuss and Düsseldorf, Germany. Specifically, we targeted the traffic problems causing adverse economic and environmental effects within the harbor area. By utilizing open-source projects and economically viable hardware, we offer a dashboard with information sourced from multiple data streams in an ad-hoc manner. We leverage crowd solving by providing ready-made solutions that each partner can acquire without technical expertise and in return provide near-real-time traffic data from which all parties can benefit. The work is part of the research project Logistics.NRW funded by Europäischer Fonds für regionale Entwicklung, Leitmarkt Mobilität & Logistik. © 2022 The Author(s).
Author Keywords	Artificial Intelligence; Crowd Solving; Logistics; SMART Urban Environment

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