Концепция построения цифрового двойника города

Сергей Александрович Иванов, Ксения Юрьевна Никольская, Глеб Игоревич Радченко, Леонид Борисович Соколинский, Михаил Леонидович Цымблер

Аннотация


В данной статье представлена концепция построения цифрового двойника города. Городское хозяйство представляет собой сложную многовекторную систему, создание единого цифрового двойника которой в настоящее время является трудно решаемой задачей. Авторами предлагается эволюционный подход к решению этой задачи, в соответствии с которым на единой программно-аппаратной платформе последовательно строятся цифровые двойники отдельных элементов городской среды. Эти цифровые двойники связываются в единую кооперативную систему, позволяющую одним цифровым двойникам использовать данные, производимые другими цифровыми двойниками. В статье дается определение и архитектура такой системы. Описываются классы моделей, которые могут использоваться для создания цифровых двойников. Особое внимание уделяется нейросетевым моделям и моделям для анализа данных. Рассматривается информационная инфраструктура цифрового двойника города, включающая в себя сенсорные сети, механизмы очистки данных и туманные вычисления.

Ключевые слова


цифровой двойник; умный город; городское управление; нейронные сети; интеллектуальный анализ данных; сенсоры; туманные вычисления

Полный текст:

PDF

Литература


Li P. Architecture of the Internet of things. M.: DMK Press, 2019. 454 p. (in Russian)

Ministry of Construction of Russia. IQ index of cities for 2018. URL: https://minstroyrf.gov.ru/docs/57570/ (accessed: 14.09.2020). (in Russian)

From concept to application solutions. Data-driven cities. 2016. URL: https://www.pwc.ru/ru/government-and-public-sector/assets/ddc_rus.pdf (accessed: 14.09.2020). (in Russian)

Povh E. Ten digital city twins. 2020. URL: https://realty.rbc.ru/news/5e297b079a79478024d54ff6 (accessed: 14.09.2020). (in Russian)

Rosatom Smart Cities. URL: https://rosatom.city/ (accessed: 14.09.2020).

Aggarwal C.C., Han J. Frequent pattern mining. Springer, 2014. 480 p. DOI: 10.1007/978-3-319-07821-2.

Agrawal R., Srikant R. Fast algorithms for mining association rules in large databases. Proceedings of 20th International Conference on Very Large Data Bases, VLDB’94 (Santiago de Chile, Chile, September, 12–15, 1994). 1994. P. 487–499.

Albawi S., Mohammed T.A., Al-Zawi S. Understanding of a convolutional neural network. The International Conference on Engineering and Technology 2017 (Antalya, Turkey, August, 21–23, 2017). 2017. P. 1–6. DOI: 10.1109/ICEngTechnol.2017.8308186.

Al-Jarrah O.Y., Yoo P.D., Muhaidat S., et al. Efficient machine learning for Big Data: A review. Big Data Research. 2015. Vol. 2, no. 3. P. 87–93. DOI: 10.1016/j.bdr.2015.04.001.

Bagloee S.A., Sarvi M., Patriksson M., et al. Optimization for roads' construction: selection, prioritization, and scheduling. Computer‐Aided Civil and Infrastructure Engineering. 2018. Vol. 33, no. 10. P. 833–848. DOI: 10.1111/mice.12370.

Batista G.E.A.P.A., Monard M.C. An analysis of four missing data treatment methods for supervised learning. Appl. Artif. Intell. 2003. Vol. 17, no. 5-6. P. 519–533. DOI: 10.1080/713827181.

Chandola V., Banerjee A., Kumar V. Anomaly detection: A survey. ACM Comput. Surv. 2009. Article no. 15. DOI: 10.1145/1541880.1541882.

Data-driven smart cities: Big Data, analytics and security. 2018. URL: https://skelia.com/articles/data-driven-smart-cities-big-data-analytics-and-security/ (accessed: 14.09.2020).

Dembski F., Wössner U., Letzgus M., et al. Urban digital twins for smart cities and citizens: the case study of Herrenberg, Germany. Sustainability. 2020. Vol. 12, art. 2307. DOI: 10.3390/su12062307.

Draper N.R., Smith H. Applied regression analysis. Wiley, 1981. 707 p.

Facebook AI Research. URL: https://ai.facebook.com/ (accessed: 20.05.2020).

Fang W., Wang L., Ren P. Tinier-YOLO: A real-time object detection method for constrained environments. IEEE Access. 2019. Vol. 8. P. 1935–1944. DOI: 10.1109/ACCESS.2019.2961959.

Fernández-Cerero D., Fernández-Montesa A., Ortega F.J., et al. Sphere: simulator of edge infrastructures for the optimization of performance and resources energy consumption. Simulation Modelling Practice and Theory. 2020. Vol. 101. P. 101966. DOI: 10.1016/j.simpat.2019.101966.

Frawley W.J., Piatetsky-Shapiro G., Matheus C.J. Knowledge Discovery in databases: an overview. Knowledge Discovery in Databases. 1991. P. 1–30.

Gardašević G., Berbakov L., Mastilović A. Cybersecurity of Industrial Internet of Things. Cyber Security of Industrial Control Systems in the Future Internet Environment. 2020. P. 47–68. DOI: 10.4018/978-1-7998-2910-2.ch003.

Glaessgen E., Stargel D. The digital twin paradigm for future NASA and U.S. air force vehicles. Proceedings of the 53rd AIAA/ASME/ASCE/AHS/ASC conference on structures, structural dynamics and materials conference (Honolulu, Hawaii, USA, April, 23–26, 2012). 2012. P. 1818. DOI: 10.2514/6.2012-1818.

Han J., Pei J., Yin Y. Mining frequent patterns without candidate generation. ACM SIGMOD Record. 2000. Vol. 29, no. 2. P. 1–12.

Hyndman R.J., Koehler A.B. Another look at measures of forecast accuracy. International Journal of Forecasting. 2006. Vol. 22, no. 4. P. 679–688. DOI: 10.1016/j.ijforecast.2006.03.001.

Iorga M., Feldman L., Barton R., et al. Fog computing conceptual model. 2018. URL: https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.500-325.pdf (accessed: 14.09.2020).

Iqbal M.N., Kütt L. End-user electricity consumption modelling for power quality analysis in residential building. 19th Int. Scientific Conf. on Electric Power Engineering, EPE. IEEE, 2018. P. 1–6. DOI: 10.1109/EPE.2018.8396030.

Kazuhiko I., Atsush Y. Building a common smart city platform utilizing FIWARE (case study of Takamatsu city). NEC Tech. J. 2018. Vol. 13, no. 1. P. 28–31.

Kim J., Tae D., Seok J. A survey of missing data imputation using generative adversarial networks. Proc. of the 2020 Int. Conf. on Artificial Intelligence in Information and Communication, ICAIIC 2020. P. 454–456. DOI: 10.1109/ICAIIC48513.2020.9065044.

Kin W., Chan V. Foundations of simulation modeling. Wiley Encyclopedia of Operations Research and Management Science. Wiley, 2011. P. 6408.

Korambath P., Wang J., Kumar A., et al. A smart manufacturing use case: furnace temperature balancing in steam methane reforming process via Kepler workflows. Procedia Computer Science. 2016. Vol. 80. P. 680–689. DOI: 10.1016/j.procs.2016.05.357.

Kuplyakov D.A., Shalnov E.V., Konushin V.S., Konushin A.S. A distributed tracking algorithm for counting people in video. Programming and Computer Software. 2019. Vol. 45, no. 4. P. 163–170. DOI: 10.1134/S0361768819040042.

Mărunţălu O., Lăzăroiu G., Manea E.E., et al. Numerical simulation of the air pollutants dispersion emitted by CHP using ANSYS CFX. World Academy of Science, Engineering and Technology, International Journal of Environmental, Chemical, Ecological, Geological and Geophysical Engineering. 2015. Vol. 9. P. 1058–1064. DOI: 10.5281/zenodo.1108252.

Mohammadi N., Taylor J.E. Smart city digital twins. Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (Honolulu, HI, USA, Nov., 27 – Dec., 1, 2017). IEEE, 2017. P. 1–5. DOI: 10.1109/SSCI.2017.8285439.

Nam T., Pardo T.A. Conceptualizing smart city with dimensions of technology, people, and institutions. Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times (College Park, MD, USA, Jun, 12–15, 2011). ACM, 2011. P. 282–291. DOI: 10.1145/2037556.2037602.

Nikouei S.Y., Chen Y., Aved A., et al. I-ViSE: interactive video surveillance as an edge service using unsupervised feature queries. IEEE Internet of Things Journal (Early Access). 2020. DOI: 10.1109/JIOT.2020.3016825.

Osman M.S., Abu-Mahfouz A.M., Page P.R. A survey on data imputation techniques: water distribution system as a use case. IEEE Access. 2018. Vol. 6. P. 63279–63291. DOI: 10.1109/ACCESS.2018.2877269.

Quinlan J. R. Induction of decision trees. Machine Learning. 1986. Vol. 1, no. 1. P. 81–106. DOI: 10.1023/A:1022643204877.

Redmon J., Farhadi A. You only look once: unified: real-time object detection. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 (Las Vegas, NV, USA, June, 27–30, 2016). P. 779–789. DOI: 10.1109/CVPR.2016.91.

Ruohomaki T., Airaksinen E., Huuska P., et al. Smart city platform enabling digital twin. 2018 International Conference on Intelligent Systems (Funchal-Madeira, Portugal, September, 25–27, 2018). IEEE, 2018. P. 155–161. DOI: 10.1109/IS.2018.8710517.

Shepelev V., Aliukov S., Glushkov A., Shabiev S. Identification of distinguishing characteristics of intersections based on statistical analysis and data from video cameras. Journal of Big Data. 2020. Vol. 7, no. 1. P. 1–23. DOI: 10.1186/s40537-020-00324-7.

Smart cities readiness: smart cities maturity model and self-assessment tool, Scottish cities alliance. 2014. URL: https://www.scottishcities.org.uk/site/assets/files/1103/smart_cities_readiness_assessment_-_guidance_note.pdf (accessed: 14.09.2020).

Wang X., Wang C. Time series data cleaning: A survey. IEEE Access. 2020. Vol. 8. P. 1866–1881. DOI: 10.1109/ACCESS.2019.2962152.

Wu Y., Kirillov A., Massa F., et al. Detectron2. URL: https://github.com/facebookresearch/detectron2 (accessed: 25.02.2020).

Yoon E.J., Kim B., Lee D.K. Multi-objective planning model for urban greening based on optimization algorithms. Urban Forestry & Urban Greening. 2019. Vol. 40. P. 183–194. DOI: 10.1016/j.ufug.2019.01.004.

Yun K., Kwon Y., Oh S., et al. Vision‐based garbage dumping action detection for realworld surveillance platform. ETRI Journal. 2019. Vol. 41, no. 4. P. 494–505. DOI: 10.4218/etrij.2018-0520.

Zaki M.J. Scalable algorithms for association mining. IEEE Transactions on Knowledge and Data Engineering. 2000. Vol. 12, no. 3. P. 372–390.

Zanella A., Bui N., Castellani A., Vangelista L., Zorzi M. Internet of things for smart cities. IEEE Internet of Things Journal. 2014. Vol. 1, no. 1. P. 22–32. DOI: 10.1109/JIOT.2014.2306328.

Zupan J. Introduction to artificial neural network methods: What they are and how to use them. Acta Chimica Slovenica. 1994. Vol. 41, no. 3. P. 327–352.




DOI: http://dx.doi.org/10.14529/cmse200401