Use of Artificial Intelligence Techniques to Yield Better Mobility Solutions
Keywords:
Smart City, Artificial Intelligence Techniques, MobilityAbstract
The term Smart City is typically applied to urban and metropolitan areas where Information and Communication Technologies provide ways to enable social, cultural and urban development, improving social and political capacities and/or efficiency. In this paper we will show the potential of Artificial Intelligence techniques for augmenting ICT solutions to both increase the cities competiveness but also the active participation of citizens in those processes, making Smart Cities smarter and convenient for the citizens.
References
- Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., and HWANG, D. (2006). Complex networks: Structure and dynamics. Physics Reports, 424(4-5):175–308.
- Carreras, I.,Gabrielli, S., Miorandi, D., Tamilin, A., Cartolano, F., Jakob, M., and Marzorati, S. (2012). SUPERHUB: a user-centric perspective on sustainable urban mobility. In Sense Transport ’12: Proceedings of the 6th ACM workshop on Next generation mobile computing for dynamic personalised travel planning. ACM.
- Diaspero, C., Heinisch, A., and Petrova, A. (2011). A Mobile Recommender System for Hiking Walkways.
- Ellul, C., Gupta, S., Haklay, M. M., and Bryson, K. (2013). A Platform for Location Based App Development for Citizen Science and Community Mapping. In Progress in Location-Based , pages 71–90. Springer Berlin Heidelberg, Berlin, Heidelberg.
- Gabrielli, L., Rinzivillo, S., Ronzano, F., and Villatoro, D. (2013). From Tweets to Semantic Trajectories: Mining Anomalous Urban Mobility Patterns. In Citizen in Sensor . . . , pages 26–35. Springer International Publishing, Cham.
- Javier Vazquez, et.al., Making Smart Cities Smarter Using Artificial Intelligence Techniques for Smarter Mobility, SMARTGREENS 2014-3rd International Conference on Smart Grids and Green IT Systems.
- MacQueen, J. (1967) Some Methods for Classification and Analysis of Multivariate Observations. Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, 1, 281-297.
- Mark S. Dougherty , Mark R. Cobbett ,Short-term inter-urban traffic forecasts using neural networks , International Journal of Forecasting, Volume 13, Issue 1, March 1997, Pages 21-31
- Mani Srivastava, Tarek Abdelzaher, and Boleslaw Szymanski, Human-centric Sensing,Philosphical Transactions of royal Society 1958,2012,pp 176-197.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRST
This work is licensed under a Creative Commons Attribution 4.0 International License.