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Visualization in Smart City Technologies

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Smart Cities (ICSC-Cities 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1555))

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Abstract

Smart cities aim to use technology to connect people with information to make evidence-based decisions, use resources more efficiently, improve citizens’ quality of life, and make cities more sustainable. Smart cities generate massive amounts of data due to a large number of embedded technology; although useful to achieve the city goals, these data are complex for people to manage. Data visualization is an efficient means to represent urban data and help people to understand the underlying information, uncover hidden patterns in data sets, and generate insights that support decision-making. This paper presents an overview of the usage of data visualization in smart city technologies, identifies the technologies used to visualize information, analyzes the visualization techniques, and offers an overview of the biggest challenges and future directions of visualization in smart cities systems.

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References

  1. Barns, S.: Smart cities and urban data platforms: designing interfaces for smart governance. City Cult. Soc. 12, 5–12 (2018)

    Article  Google Scholar 

  2. Batty, M., Hudson-Smith, A., Hugel, S., Roumpani, F.: Visualising Data for Smart Cities, pp. 453–475. IGI Global, Hershey (2018)

    Google Scholar 

  3. Bocconi, S., Bozzon, A., Psyllidis, A., Titos Bolivar, C., Houben, G.J.: Social glass: a platform for urban analytics and decision-making through heterogeneous social data. In: Proceedings of the 24th International Conference on World Wide Web, pp. 175–178. WWW2015 Companion, Association for Computing Machinery, New York (2015)

    Google Scholar 

  4. Camero, A., Alba, E.: Smart city and information technology: a review. Cities 93, 84–94 (2019)

    Article  Google Scholar 

  5. Chang, W.: R Graphics Cookbook: Practical Recipes for Visualizing Data. O’Reilly Media, Farnham (2018)

    Google Scholar 

  6. Chen, W., Guo, F., Wang, F.Y.: A survey of traffic data visualization. IEEE Trans. Intell. Transp. Syst. 16(6), 2970–2984 (2015)

    Article  Google Scholar 

  7. Cheng, B., Longo, S., Cirillo, F., Bauer, M., Kovacs, E.: Building a big data platform for smart cities: experience and lessons from santander. In: 2015 IEEE International Congress on Big Data, pp. 592–599 (2015)

    Google Scholar 

  8. Chun, S.A., Lyons, K., Adam, N.R.: The smart city of Newark, NJ: data analytics platform for economic development and policy assessment. In: Anthopoulos, L. (ed.) Smart City Emergence, pp. 315–331. Elsevier, Amsterdam (2019)

    Google Scholar 

  9. Dunne, C., Skelton, C., Diamond, S., Meirelles, I., Martino, M.: Quantitative, qualitative, and historical urban data visualization tools for professionals and stakeholders. In: Streitz, N., Markopoulos, P. (eds.) Distributed, Ambient and Pervasive Interactions, pp. 405–416. Springer International Publishing, Cham (2016)

    Chapter  Google Scholar 

  10. Eberhardt, A., Silveira, M.S.: Show me the data! A systematic mapping on open government data visualization. In: Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age. DGO 2018, Association for Computing Machinery, New York (2018)

    Google Scholar 

  11. Evertzen, W.H.N., Effing, R., Constantinides, E.: The internet of things as smart city enabler: the cases of Palo Aalto, Nice and Stockholm. In: Digital Transformation for a Sustainable Society in the 21st Century. pp. 293–304. Springer International Publishing, Cham (2019). https://doi.org/10.1007/978-3-030-29374-1

  12. Few, S.: Dashboard Confusion Revisited. Perceptual Edge pp. 1–6 (2007)

    Google Scholar 

  13. Fortini, P.M.A., Davis, C.A.: Analysis, integration and visualization of urban data from multiple heterogeneous sources. In: Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities, pp. 17–26. ARIC 2018, Association for Computing Machinery, New York (2018)

    Google Scholar 

  14. Ghosh, D., Chun, S.A., Shafiq, B., Adam, N.R.: Big data-based smart city platform: real-time crime analysis. In: Proceedings of the 17th International Digital Government Research Conference on Digital Government Research, pp. 58–66. Association for Computing Machinery, New York (2016)

    Google Scholar 

  15. Ghosh, P., Mahesh, T.: Smart city: concept and challenges. Int. J. Adv. Eng. Technol. Sci. 1(1), 25–27 (2015)

    Google Scholar 

  16. González-Briones, A., Chamoso, P., Casado-Vara, R., Rivas, A., Omatu, S., Corchado, J.M.: Internet of Things Platform to Encourage Recycling in a Smart City, pp. 414–423. Elsevier, Amsterdam (2019)

    Google Scholar 

  17. Gouveia, J.P., Seixas, J., Giannakidis, G.: Smart city energy planning: integrating data and tools. In: Proceedings of the 25th International Conference Companion on World Wide Web, WWW 2016. pp. 345–350. International World Wide Web Conferences Steering Committee (2016)

    Google Scholar 

  18. Grainger, S., Mao, F., Buytaert, W.: Environmental data visualisation for non-scientific contexts: literature review and design framework. Environ. Model. Softw. 85, 299–318 (2016)

    Article  Google Scholar 

  19. Habibzadeh, H., Kaptan, C., Soyata, T., Kantarci, B., Boukerche, A.: Smart city system design: a comprehensive study of the application and data planes. ACM Comput. Surv. 52(2) (2019)

    Google Scholar 

  20. Harrison, C., et al.: Foundations for smarter cities. IBM J. Res. Dev. 54(4), 1–16 (2010)

    Article  Google Scholar 

  21. Kim, S.A., Shin, D., Choe, Y., Seibert, T., Walz, S.P.: Integrated energy monitoring and visualization system for smart green city development: designing a spatial information integrated energy monitoring model in the context of massive data management on a web based platform. Autom. Constr. 22, 51–59 (2012)

    Article  Google Scholar 

  22. Kitchenham, B.: Procedures for performing systematic reviews. Tech. Rep. 0400011T.1, Keele University, Keele, July 2004

    Google Scholar 

  23. Lim, C., Kim, K.J., Maglio, P.P.: Smart cities with big data: reference models, challenges, and considerations. Cities 82, 86–99 (2018)

    Article  Google Scholar 

  24. Liono, J., Salim, F.D., Subastian, I.F.: Visualization oriented spatiotemporal urban data management and retrieval. In: Proceedings of the ACM First International Workshop on Understanding the City with Urban Informatics, pp. 21–26. UCUI 2015, Association for Computing Machinery, New York (2015)

    Google Scholar 

  25. Liu, X., Nielsen, P.S.: Air quality monitoring system and benchmarking. In: Bellatreche, L., Chakravarthy, S. (eds.) Big Data Analytics and Knowledge Discovery, pp. 459–470. Springer International Publishing, Cham (2017)

    Chapter  Google Scholar 

  26. Lv, Z., Li, X., Wang, W., Zhang, B., Hu, J., Feng, S.: Government affairs service platform for smart city. Fut. Gener. Comput. Syst. 81, 443–451 (2018)

    Article  Google Scholar 

  27. Ma, M., Preum, S.M., Ahmed, M.Y., Tärneberg, W., Hendawi, A., Stankovic, J.A.: Data sets, modeling, and decision making in smart cities: a survey. ACM Trans. Cyber-Phys. Syst. 4(2) (2019)

    Google Scholar 

  28. Marras, M., Manca, M., Boratto, L., Fenu, G., Laniado, D.: Barcelonanow: empowering citizens with interactive dashboards for urban data exploration. In: Companion Proceedings of the the Web Conference 2018, WWW 2018. pp. 219–222. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE (2018)

    Google Scholar 

  29. Matheus, R., Janssen, M., Maheshwari, D.: Data science empowering the public: data-driven dashboards for transparent and accountable decision-making in smart cities. Govt. Inf. Q. 37(3), 101284 (2020)

    Google Scholar 

  30. McArdle, G., Kitchin, R.: The dublin dashboard: design and development of a real-time analytical urban dashboard. In: First International Conference on Smart Data and Smart Cities; ISPRS Annals Photogrammetry, Remote Sensing and Spatial Information Sciences, III-4/W1, pp. 19–25. September 2016

    Google Scholar 

  31. Ming, F.X., Habeeb, R.A.A., Md Nasaruddin, F.H.B., Gani, A.B.: Real-time carbon dioxide monitoring based on IoT & cloud technologies. In: Proceedings of the 8th International Conference on Software and Computer Applications, ICSCA 2019, pp. 517–521, Association for Computing Machinery, New York (2019)

    Google Scholar 

  32. Moustaka, V., Vakali, A., Anthopoulos, L.G.: Citydna: smart city dimensions’ correlations for identifying urban profile. In: Proceedings of the 26th International Conference on World Wide Web Companion, WWW 2017, pp. 1167–1172. Companion, International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE (2017)

    Google Scholar 

  33. Obie, H.O., Chua, C., Avazpour, I., Abdelrazek, M., Grundy, J., Bednarz, T.: Pedaviz: visualising hour-level pedestrian activity. In: Proceedings of the 11th International Symposium on Visual Information Communication and Interaction, VINCI 2018, pp. 9–16. ACM, New York (2018)

    Google Scholar 

  34. Panagiotou, N., et al.: Intelligent urban data monitoring for smart cities. In: Berendt, B., et al. (eds.) Machine Learning and Knowledge Discovery in Databases, pp. 177–192. Springer International Publishing, Cham (2016)

    Chapter  Google Scholar 

  35. Pardo-García, N., Simoes, S.G., Dias, L., Sandgren, A., Suna, D., Krook-Riekkola, A.: Sustainable and resource efficient cities platform – SureCity holistic simulation and optimization for smart cities. J. Clean. Prod. 215, 701–711 (2019)

    Article  Google Scholar 

  36. Peddoju, S.K., Upadhyay, H.: Evaluation of iot data visualization tools and techniques. In: Anouncia, S.M., Gohel, H.A., Vairamuthu, S. (eds.) Data Visualization, pp. 115–139. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-2282-6_7

    Chapter  Google Scholar 

  37. Petrolo, R., Loscri, V., Mitton, N.: Towards a smart city based on cloud of things, a survey on the smart city vision and paradigms. Trans. Emerg. Telecommun. Technol. 28(1), 294–307 (2017)

    Google Scholar 

  38. Pettit, C., Widjaja, I., Russo, P., Sinnott, R., Stimson, R., Tomko, M.: Visualisation support for exploring urban space and place. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. vol. 1, pp. 153–158 (2012)

    Google Scholar 

  39. Pettit, C., et al.: Planning support systems for smart cities. City Cult. Soc. 12, 13–24 (2018)

    Article  Google Scholar 

  40. Pettit, C., Lieske, S.N., Jamal, M.: CityDash: Visualising a Changing City Using Open Data, pp. 337–353. Springer International Publishing, Berlin (2017)

    Google Scholar 

  41. Pinto, A.L., Gonzales-Aguilar, A., Lima Dutra, M., Ribas Semeler, A., Denisczwicz, M., Closel, C.: The Visualization of Information of the Internet of Things, Chap. 5, pp. 117–137. John Wiley & Sons, Ltd., New York (2017)

    Google Scholar 

  42. Popa, C.L., Carutasu, G., Cotet, C.E., Carutasu, N.L., Dobrescu, T.: Smart city platform development for an automated waste collection system. Sustainability 9(11), 2064 (2017)

    Article  Google Scholar 

  43. Protopsaltis, A., Sarigiannidis, P., Margounakis, D., Lytos, A.: Data visualization in internet of things: tools, methodologies, and challenges. In: Proceedings of the 15th International Conference on Availability, Reliability and Security. ARES 2020, Association for Computing Machinery, New York (2020)

    Google Scholar 

  44. Raj, P., Kumar, S.A.P.: Big Data Analytics Processes and Platforms Facilitating Smart Cities, chap. 2, pp. 23–52. John Wiley & Sons, Ltd (2017)

    Google Scholar 

  45. Ram, S., Wang, Y., Currim, F., Dong, F., Dantas, E., Sabóia, L.A.: Smartbus: a web application for smart urban mobility and transportation. In: 25th International Conference on World Wide Web Companion. WWW 2016, pp. 363–368. Companion, International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE (2016)

    Google Scholar 

  46. Rhazal, O.E., Tomader, M.: Study of smart city data: categories and quality challenges. In: Proceedings of the 4th International Conference on Smart City Applications. SCA 2019, Association for Computing Machinery, New York (2019)

    Google Scholar 

  47. Sachsenmeier, R., Marinescu, L., Oliveira, J., Silva, M., Verhijde, M.: Smart cities. In: Guide to Open Government, Chap. 3, pp. 4–18. Lifelong Learning Program (2015)

    Google Scholar 

  48. Saggi, M.K., Jain, S.: A survey towards an integration of big data analytics to big insights for value-creation. Inf. Process. Manag. 54(5), 758–790 (2018). (Big) Data we trust: Value creation in knowledge organizations

    Google Scholar 

  49. Sanaei, S., Majidi, B., Akhtarkavan, E.: Deep multisensor dashboard for composition layer of web of things in the smart city. In: 2018 9th International Symposium on Telecommunications (IST), pp. 211–215 (2018)

    Google Scholar 

  50. Santana, E.F.Z., Chaves, A.P., Gerosa, M.A., Kon, F., Milojicic, D.S.: Software platforms for smart cities: concepts, requirements, challenges, and a unified reference architecture. ACM Comput. Surv. 50(6) (2017)

    Google Scholar 

  51. Schunke, L.C., de Oliveira, L.P.L., Villamil, M.B.: Visualization and analysis of interacting occurrences in a smart city. In: 2014 IEEE Symposium on Computers and Communications (ISCC), pp. 1–7, June 2014

    Google Scholar 

  52. Sharifi, A.: A typology of smart city assessment tools and indicator sets. Sustain. Cities Soc. 53, 101936 (2020)

    Google Scholar 

  53. Steptoe, M., Krüger, R., Garcia, R., Liang, X., Maciejewski, R.: A visual analytics framework for exploring theme park dynamics. ACM Trans. Interact. Intell. Syst. 8(1) (2018)

    Google Scholar 

  54. Suciu, G., Necula, L., Usurelu, T., Rogojanu, I., Diţu, M., Vulpe, A.: IoT-based 3d visualisation platform for an efficient management of the smart city ecosystem. In: 2018 Global Wireless Summit (GWS), pp. 37–42 (2018)

    Google Scholar 

  55. Tong, X., Wu, Z.: Study of chinese city “portrait" based on data visualization: take city dashboard for example. In: Marcus, A., Wang, W. (eds.) DUXU 2018. LNCS, vol. 10919, pp. 353–364. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91803-7_26

    Chapter  Google Scholar 

  56. Trencher, G.: Towards the smart city 2.0: empirical evidence of using smartness as a tool for tackling social challenges. Technol. Forecast. Soc. Change 142, 117–128 (2019)

    Google Scholar 

  57. Trilles, S., Calia, A., Belmonte, Ó., Torres-Sospedra, J., Montoliu, R., Huerta, J.: Deployment of an open sensorized platform in a smart city context. Fut. Gener. Comput. Syst. 76, 221–233 (2017)

    Article  Google Scholar 

  58. Vila, R.A., Estevez, E., Fillottrani, P.R.: The design and use of dashboards for driving decision-making in the public sector. In: Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2018. pp. 382–388. ACM, New York (2018)

    Google Scholar 

  59. Young, G.W., Kitchin, R., Naji, J.: Building city dashboards for different types of users. J. Urban Technol. 28, 1–21 (2020)

    Google Scholar 

  60. Zaldei, A., et al.: An integrated low-cost road traffic and air pollution monitoring platform to assess vehicles air quality impact in urban areas. In: 20th EURO Working Group on Transportation Meeting, EWGT. vol. 27, pp. 609–616 (2017)

    Google Scholar 

  61. Zdraveski, V., Mishev, K., Trajanov, D., Kocarev, L.: ISO-standardized smart city platform architecture and dashboard. IEEE Perv. Comput. 16(2), 35–43 (2017)

    Article  Google Scholar 

  62. Zhang, J., Chen, Z., Liu, Y., Du, M., Yang, W., Guo, L.: Space-time visualization analysis of bus passenger big data in Beijing. Cluster Comput. 21(1), 813–825 (2018)

    Article  Google Scholar 

  63. Zhong, C., Wang, T., Zeng, W., Müller Arisona, S.: Spatiotemporal Visualisation: A Survey and Outlook. In: Arisona, S.M., Aschwanden, G., Halatsch, J., Wonka, P. (eds.) Digital Urban Modeling and Simulation. CCIS, vol. 242, pp. 299–317. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-29758-8_16

    Chapter  Google Scholar 

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  1. Facultad de Estadística e Informática, Universidad Veracruzana, Xalapa, Mexico

    Teresa Cepero, Luis G. Montané-Jiménez, Edgard Benítez-Guerrero & Carmen Mezura-Godoy

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  1. Teresa Cepero
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Correspondence to Luis G. Montané-Jiménez .

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  1. Universidad de la República, Montevideo, Uruguay

    Sergio Nesmachnow

  2. University of Valladolid, Soria, Spain

    Luis Hernández Callejo

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Cepero, T., Montané-Jiménez, L.G., Benítez-Guerrero, E., Mezura-Godoy, C. (2022). Visualization in Smart City Technologies. In: Nesmachnow, S., Hernández Callejo, L. (eds) Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555. Springer, Cham. https://doi.org/10.1007/978-3-030-96753-6_7

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  • DOI: https://doi.org/10.1007/978-3-030-96753-6_7

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