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Crowdsourcing for Smart Cities That Realizes the Situation of Cities and Information Sharing

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Handbook of Smart Cities

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.

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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.

    Chapter  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273–297.

    MATH  Google Scholar 

  • Feng, F. (2013). Winter road surface condition estimation and forecasting. PhD thesis, University of Waterloo, Ontario

    Google Scholar 

  • Greengard, S. (2014). Weathering a new era of big data. Communications of the ACM, 57(9), 12âĂŞ14. https://doi.org/10.1145/2641225.

    Article  Google Scholar 

  • 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.

    Chapter  Google Scholar 

  • 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.

    Google Scholar 

  • Howe, J. (2008). Crowdsourcing: How the power of the crowd is driving the future of business. London: Random House.

    Google Scholar 

  • 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).

    Google Scholar 

  • 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.

    Chapter  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Chapter  Google Scholar 

  • Lang, P. J. (1995). The emotion probe: Studies of motivation and attention. American Psychologist, 50(5), 372–385.

    Article  Google Scholar 

  • Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2), 1–135.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  MathSciNet  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Chapter  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

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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.

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Correspondence to Kenro Aihara .

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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

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  • DOI: https://doi.org/10.1007/978-3-030-15145-4_67-1

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