Abstract
Besides vehicles, buildings are one of the main energy users in urban areas. The rate of energy usage of a particular building depends on features such as human activities, the number of people inside, weather, and the surrounding landscape. Such complex interactions makes energy usage of buildings hard to understand. In this work, we analyze the energy usage of Chicago loop under the effects of several features. Through our extensive experiments, we explore the connections between energy usage and these features. Moreover, we proposed an algorithm that assigns vehicles to buildings by considering three parameters: location of the building, its size, and land-use.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Amasyali, K., El-Gohary, N.M.: A review of data-driven building energy consumption prediction studies. Renew. Sustain. Energy Rev. 81, 1192–1205 (2018)
Becerik-Gerber, B., et al.: Civil engineering grand challenges: opportunities for data sensing, information analysis, and knowledge discovery. J. Comput. Civ. Eng. 28(4), 04014013 (2014)
Berres, A., et al.: A mobility-driven approach to modeling building energy. In: 2019 IEEE International Conference on Big Data (Big Data), pp. 3887–3895 IEEE (2019)
Castleton, H.F., et al.: Green roofs; building energy savings and the potential for retrofit. Energy Build. 42(10), 1582–1591 (2010)
Cho, E., Myers, S.A., Leskovec, J.: Friendship and mobility: user movement in location-based social networks. In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1082–1090 (2011)
City of Chicago: Data Terms of Use, 22 July 2020. https://www.chicago.gov/city/en/narr/foia/data_disclaimer.html. Accessed on 23 Jul 2020
Crawley, D.B., et al.: Contrasting the capabilities of building energy performance simulation programs. Build. Environ. 43(4), 661–673 (2008)
Doan, T.N., Lim, E.P.: Attractiveness versus competition: towards an unified model for user visitation. In: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. CIKM 2016, Indianapolis, Indiana, USA, pp. 2149–2154. Association for Computing Machinery (2016)
CMAP Data Hub: Land use inventory for northeast Illinois, 2013 - CMAP Data Hub, 23 July 2020. https://datahub.cmap.illinois.gov/dataset/land-use/resource/5716abb3-a432-46b2-ab47-d268de302b94. Accessed on 23 Jul 2020
Sadineni, S.B., Madala, S., Boehm, R.F.: Passive building energy savings: a review of building envelope components. Renew. Sustain. Energy Rev. 15(8), 3617–3631 (2011)
Stiglic, M., et al.: Enhancing urban mobility: integrating ride-sharing and public transit. Comput. Oper. Res. 90, 12–21 (2018)
QGIS Development Team et al.: QGIS geographic information system. Open Source Geospatial Foundation Project (2016)
Wei, H., et al.: Intellilight: a reinforcement learning approach for intelligent traffic light control. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 2496–2505 (2018)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Alharin, A., Patel, Y., Doan, TN., Sartipi, M. (2020). Data Analysis and Visualization of Traffic in Chicago with Size and Landuse-Aware Vehicle to Buildings Assignment. In: Nichols, J., Verastegui, B., Maccabe, A.‘., Hernandez, O., Parete-Koon, S., Ahearn, T. (eds) Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI. SMC 2020. Communications in Computer and Information Science, vol 1315. Springer, Cham. https://doi.org/10.1007/978-3-030-63393-6_35
Download citation
DOI: https://doi.org/10.1007/978-3-030-63393-6_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-63392-9
Online ISBN: 978-3-030-63393-6
eBook Packages: Computer ScienceComputer Science (R0)