Abstract
The chapter describes initiatives aimed at improving the quality and efficiency of urban life by understanding the urban situation by utilizing an unspecified number of citizens and sharing collected and aggregated information, mainly using commoditized devices such as smartphones. Specifically, the chapter focuses on efforts to improve the efficiency of road management work by collecting road traffic conditions using a drive recorder application and acquiring sensor data that can estimate the road surface condition. It also shows a crowdsourced bus location service that can be realized at low cost by making good use of BLE beacons and smartphone apps. In addition, the chapter focuses on efforts to collect the “emotions” of people who go and go on the street corner.
References
Aihara, K., Imura, H., Takasu, A., Tanaka, Y., & Adachi, J. (2014). Crowdsourced mobile sensing for smarter city life. In 2014 IEEE 7th international conference on service-oriented computing and applications (pp. 334–337). Piscataway: IEEE.
Aihara K., Bin P., Imura H., Takasu A., Tanaka Y. (2018) Collecting Bus Locations by Users: A Crowdsourcing Model to Estimate Operation Status of Bus Transit Service. In: Streitz N., Konomi S. (Eds.), Distributed, Ambient and Pervasive Interactions: Understanding Humans. DAPI 2018. Lecture Notes in Computer Science, vol 10921. Cham: Springer. https://doi.org/10.1007/978-3-319-91125-0_14
Amichai-Hamburger, Y. (2008). Potential and promise of online volunteering. Computers in Human Behavior, 24(2), 544–562.
Chang, C. C., & Lin, C. J. (2011). Libsvm: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2(3), 27:1–27:27.
Conti, M., Das, S. K., Bisdikian, C., Kumar, M., Ni, L. M., Passarella, A., Roussos, G., Tröster, G., Tsudik, G., & Zambonelli, F. (2012). Looking ahead in pervasive computing: Challenges and opportunities in the era of cyber-physical convergence. Pervasive and Mobile Computing, 8(1), 2–21. https://doi.org/10.1016/j.pmcj.2011.10.001. http://www.sciencedirect.com/science/article/pii/S1574119211001271.
Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273–297.
Feng, F. (2013). Winter road surface condition estimation and forecasting. PhD thesis, University of Waterloo, Ontario
Greengard, S. (2014). Weathering a new era of big data. Communications of the ACM, 57(9), 12âĂŞ14. https://doi.org/10.1145/2641225.
He, Z., & Jin, L. (2009). Activity recognition from acceleration data based on discrete consine transform and svm. In The 2009 IEEE international conference on systems, man, and cybernetics (pp. 5041–5044). http://ieeexplore.ieee.org/xpl/downloadCitations.
Honda Motor Co, Ltd. (2013). A traffic safety map made by everyone. http://world.honda.com/safety/hearts/2013/03/index.html
Howe, J. (2006a). ‘Crowdsourcing: A Definition’, Crowdsourcing: Tracking the Rise of the Amateur (weblog, 2 June), URL: http://crowdsourcing.typepad.com/cs/2006/06/crowdsourcing_a.html. Accessed 24 Nov 2006.
Howe, J. (2006b). The rise of crowdsourcing. Wired Magazine, 14(6), 1–4.
Howe, J. (2008). Crowdsourcing: How the power of the crowd is driving the future of business. London: Random House.
Kanatani, N., Sasama, T., Kawamura, T., & Sugahara, K. (2010). Development of bus location system using smart phones. In Proceedings of SICE annual conference 2010, Taipei, Taiwan: IEEE, (pp. 2432–2433).
King, S. F., & Brown, P. (2007). Fix my street or else: Using the internet to voice local public service concerns. In Proceedings of the 1st international conference on theory and practice of electronic governance (pp. 72–80). https://doi.org/10.1145/1328057.1328076.
Kinoshita, A., Takasu, A., & Adachi, J. (2014). Traffic incident detection using probabilistic topic model. In The workshop proceedings of the EDBT/ICDT 2014 joint conference (pp. 323–330). http://ceur-ws.org/Vol-1133/paper-52.pdf.
Koyanagi, T., Kobayashi, Y., Miyagi, S., & Yamamoto, G. (2005). Agent server for a location-aware personalized notification service. In T. Ishida, L. Gasser, & H. Nakashima (Eds.), Massively multi-agent systems I (pp. 224–238). Berlin/Heidelberg: Springer Berlin Heidelberg.
Lang, P. J. (1995). The emotion probe: Studies of motivation and attention. American Psychologist, 50(5), 372–385.
Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2), 1–135.
Piao, B., & Aihara, K. (2017). Detecting the road surface condition by using mobile crowdsensing with drive recorder. 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), Yokohama, 1–8. https://doi.org/10.1109/ITSC.2017.8317818
Poovendran, R. (2010). Cyber-physical systems: Close encounters between two parallel worlds. Proceedings of the IEEE, 98(8), 1363–1366. https://doi.org/10.1109/JPROC.2010.2050377.
Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161–1178. https://doi.org/10.1037/h0077714.
Saragih, J. M., Lucey, S., & Cohn, J. F. (2011). Deformable model fitting by regularized landmark mean-shift. International Journal of Computer Vision, 91(2), 200–2015.
Schuurman, D., Baccarne, B., De Marez, L., & Mechant, P. (2012). Smart ideas for smart cities: Investigating crowdsourcing for generating and selecting ideas for ict innovation in a city context. Journal of Theoretical and Applied Electronic Commerce Research, 7(3), 49–62.
Shigihara, I., Arai, A., Saitou, O., Kuwahara, Y., & Kamada, M. (2013). A dynamic bus guide based on real-time bus locations – A demonstration plan. In 2013 16th international conference on network-based information systems (NBIS) (pp. 436–438). https://doi.org/10.1109/NBiS.2013.71.
Stembert, N., & Mulder, I. J. (2013). Love your city! An interactive platform empowering citizens to turn the public domain into a participatory domain. In International conference using ICT, social media and mobile technologies to Foster self-organisation in urban and neighbourhood governance. http://resolver.tudelft.nl/uuid:23c4488b-09e1-4b90-85e3-143e4a144215.
Watkins, K. E., Ferris, B., Borning, A., Rutherford, G. S., & Layton, D. (2011). Where is my bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders. Transportation Research Part A: Policy and Practice, 45(8), 839–848. https://doi.org/10.1016/j.tra.2011.06.010. http://www.sciencedirect.com/science/article/pii/S0965856411001030.
Yamada, M., Ueda, K., Horiba, I., Tsugawa, S., & Yamamoto, S. (2004). A study of the road surface condition detection technique based on the image information for deployment on a vehicle. IEEJ Transactions on Electronics, Information and Systems, 124(3), 753–760. https://doi.org/10.1541/ieejeiss.124.753.
Zhu, Y., Zhang, S., Li, Y., Lu, H., Shi, K., & Niu, Z. (2020). Social weather: A review of crowdsourcing-assisted meteorological knowledge services through social cyberspace. Geoscience Data Journal, 7(1), 61–79. https://doi.org/10.1002/gdj3.85.
Acknowledgments
The author would like to thank the City of Sapporo, Hokkaido Government, and Hokkaido Chuo Bus Co., Ltd. for their cooperation with projects in Sapporo. The author also thanks KDDI R&D Laboratories, Shibasaki Laboratory of Center for Spatial Information Science of the University of Tokyo, Tokyo Corporation, the National Institute of Advanced Industrial Science and Technology (AIST), and JIPDEC for their cooperation with Nicott project.
The research projects were partly supported by the CPS-IIP Project in the research promotion programs “Research and Development for the Realization of Next-Generation IT Platforms” of the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT), “Research and Development on Fundamental and Utilization Technologies for Social Big Data” of the Commissioned Research Promotion Office of the National Institute of Information and Communications Technology (NICT), Japan, and the Grant-in-Aid for IT Integration-based New Social System Development and Demonstration Project of the New Energy and Industrial Technology Development Organization (NEDO) of Japan.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this entry
Cite this entry
Aihara, K., Imura, H. (2021). Crowdsourcing for Smart Cities That Realizes the Situation of Cities and Information Sharing. In: Augusto, J.C. (eds) Handbook of Smart Cities. Springer, Cham. https://doi.org/10.1007/978-3-030-15145-4_67-1
Download citation
DOI: https://doi.org/10.1007/978-3-030-15145-4_67-1
Received:
Accepted:
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-15145-4
Online ISBN: 978-3-030-15145-4
eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering