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Issue No.06 - Nov.-Dec. (2013 vol.17)
pp: 22-29
Vassilis Kostakos , University of Oulu
Timo Ojala , University of Oulu
Tomi Juntunen , University of Oulu
Smart city technologies can provide substantial benefits that improve people's daily lives. Here, the authors investigate how ubiquitous traffic sensing technologies and techniques can be incorporated with conventional traffic control and monitoring practices in the city of Oulu, Finland. In collaboration with the city's traffic control center and traffic planners, they exploit inductive magnetic sensing and Wi-Fi scanning across the city center, and develop tools to assist traffic operators in their tasks.
Internet, Cities and towns, Remote sensing, Sensors, Urban areas, Traffic control, Smart buildings,tools, traffic, mobility, control center, ubiquitous computing
Vassilis Kostakos, Timo Ojala, Tomi Juntunen, "Traffic in the Smart City: Exploring City-Wide Sensing for Traffic Control Center Augmentation", IEEE Internet Computing, vol.17, no. 6, pp. 22-29, Nov.-Dec. 2013, doi:10.1109/MIC.2013.83
1. T. Prevot, “Exploring the Many Perspectives of Distributed Air Traffic Management: The Multi Aircraft Control System MACS,” Proc. Int’l Conf. Human-Computer Interaction in Aerospace (HCI-Aero), AAAI, 2002, pp. 149-154.
2. W.E. MacKay, “Is Paper Safer? The Role of Paper Flight Strips in Air Traffic Control,” ACM Trans. Computer-Human Interaction, vol. 6, 1999, pp. 311-340.
3. R. Bentley et al., “Ethnographically-Informed Systems Design for Air Traffic Control,” Proc. 1992 ACM Conf. Computer-Supported Cooperative Work, ACM, 1992, pp. 123-129.
4. W.E. Mackay et al., “Reinventing the Familiar: Exploring an Augmented Reality Design Space for Air Traffic Control,” Proc. SIGCHI Conf. Human Factors in Computing Systems, ACM, 1998, pp. 558-565.
5. M. Wahlström et al., “Resolving Safety-Critical Incidents in a Rally Control Center,” Human-Computer Interaction, vol. 26, 2011, pp. 9-37.
6. R. Bolla and F. Davoli, “Road Traffic Estimation from Location Tracking Data in the Mobile Cellular Network,” Proc. Wireless Communications and Networking Conf., IEEE, vol. 3, 2000, pp. 1107-1112.
7. F. Calabrese et al., “Estimating Origin-Destination Flows Using Mobile Phone Location Data,” IEEE Pervasive Computing, Oct–Dec. 2011, pp. 36-44.
8. V. Kostakos et al., “Brief Encounters: Sensing, Modeling, and Visualizing Urban Mobility and Copresence Networks,” ACM Trans. Computer-Human Interaction, vol. 17, 2010, p. 2.
9. S. Lorkowski et al., “Towards Area-Wide Traffic Monitoring Applications Derived from Probe Vehicle Data,” Proc. 8th Int’l Conf. Applications of Advanced Technologies in Transportation Eng., ACSE, 2004, pp. 389-394.
10. M. Schlossberg and N. Brown, “Comparing Transit-Oriented Development Sites by Walkability Indicators,” Transportation Research Record, vol. 1887, 2004, pp. 34-42.
11. F. Girardin et al., “Digital Footprinting: Uncovering Tourists with User-Generated Content,” IEEE Pervasive Computing, Oct.–Dec. 2008, pp. 36-43.
12. G.D. Abowd, “What Next, Ubicomp? Celebrating an Intellectual Disappearing Act,” Proc. 2012 ACM Conf. Ubiquitous Computing, ACM, 2012, pp. 31-40.
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