OPEN-ACCESS PEER-REVIEWED
Mrs K. Sri Durga1*, Dr. A. V. N. Murty2, Dr. Santanu Roy3, Prof. Murshaduddin Killedar4, TNVR Swamy5, Mythreya Savaram6
1*Research Scholar, Department of Management Studies, KL University
2Professor in Management K.L.E.F deemed University
3Professor, ICFAI Business School (IBS), The ICFAI University, Dehradun, India,
4Founder and CEO of Skilloxy, Dharwad, Karnataka, India.
5Professor, VIT Business School, VIT Vellore, Tamil Nadu
6Assistant Professor, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
Abstract
Urban planning and development are experiencing unprecedented challenges due to the increasing trends of global urbanization, and therefore, the integration of big data analytics as a critical approach to decision-making. This review explores the uses, advantages, limitations, and possibilities of big data analysis in cities. Big data analytics uses large and diverse data sets from IoT sensors, satellite images, social media, and administrative records to improve the efficiency of urban systems. Some of the key uses are in the improvement of transport systems, management of infrastructures, forecasting housing needs, health intervention, and economic growth. New York City, Singapore, and Barcelona are examples that show how the use of big data can contribute to the creation of sustainable solutions for urban environments and the enhancement of the quality of life of citizens. However, the integration of big data analytics has challenges like data privacy, data quality, and the expertise of a technical professional. Moving ahead, the integration of big data, predictive analysis, and IoT will bring a paradigm shift in urban management and will help in building smart and sustainable cities. Ethical issues are still important to maintain the correct approach to the use of data, as well as to maintain the principles of transparency and fairness in urban planning.
Keywords: Big data analytics, Urban planning, Smart cities, Predictive analytics, IoT (Internet of Things)
References
[1]. Al Nuaimi, E., Al Neyadi, H., Mohamed, N. et al. Applications of big data to smart cities. J Internet Serv Appl 6, 25 (2015). https://doi.org/10.1186/s13174-015-0041-5
[2]. Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of Urban Technology, 22(1), 3-21.
[3]. Alsunaidi, S. J., Almuhaideb, A. M., Ibrahim, N. M., Shaikh, F. S., Alqudaihi, K. S., Alhaidari, F. A., Khan, I. U., Aslam, N., & Alshahrani, M. S. (2021). Applications of Big Data Analytics to Control COVID-19 Pandemic. Sensors (Basel, Switzerland), 21(7), 2282. https://doi.org/10.3390/s21072282
[4]. Batty, M., Axhausen, K. W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M.,
[5]. … & Portugali, Y. (2012). Smart cities of the future. European Physical Journal Special Topics, 214(1), 481-518.
[6]. Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15(5), 662-679. Cao, X., Wang, M., & Liu, X. (2020).
[7]. Application of Big Data Visualization in Urban Planning. IOP Conference Series. Earth and Environmental Science, 440(4), 042066. https://doi.org/10.1088/1755- 1315/440/4/042066 CC BY 4.0 Deed | Attribution 4.0 International | Creative Commons. (n.d.). Retrieved from https://creativecommons.org/licenses/by/4.0/
[8]. Cesario, E. (2023). Big data analytics and smart cities: applications, challenges, and opportunities. Frontiers in Big Data, 6. https://doi.org/10.3389/fdata.2023.1149402 Chen, C., Zhang, C., Bu, T., & Li, X. (2017).
[9]. Real-time traffic flow data based on GIS and internet of things: A case study of Macao. Sustainability, 9(3), 430.
[10]. Cho, H., Ippolito, D., & Yu, Y. W. (2020). Contact tracing mobile apps for COVID-19: Privacy considerations and related trade-offs. arXiv preprint arXiv:2003.11511.
[11]. Cisco. (2011). Cisco visual networking index: Global mobile data traffic forecast update, 2010-2015. Retrieved from https://www.cisco.com/c/en/us/solutions/co llateral/service-provider/visual-networking- index-vni/white_paper_c11-520862.html
[12]. Darvazeh, S. S., Vanani, I. R., & Musolu, F. M. (2020). Big Data Analytics and Its Applications in Supply Chain Management. In IntechOpen eBooks. https://doi.org/10.5772/intechopen.89426
[13]. Elena, V., Singh, R., Sobti, R., Sharma, K., Sharma, R., & Surekha, P. (2024). Leveraging Big Data Analytics for Urban Planning: A Study Using the Big Data Analytics Efficiency Test. Bio Web of Conferences/BIO Web of Conferences, 86, 01082. https://doi.org/10.1051/bioconf/2024860108 2
[14]. Elena, V., Singh, R., Sobti, R., Sharma, K., Sharma, R., & Surekha, P. (2024b). Leveraging Big Data Analytics for Urban Planning: A Study Using the Big Data Analytics Efficiency Test. Bio Web of Conferences/BIO Web of Conferences, 86, 01082. https://doi.org/10.1051/bioconf/2024860108 2
[15]. Feng, X., Liu, J., & Wang, Y. (2018). A review on big data-driven urban traffic management: Concept, methods and application. IEEE Access, 6, 28876-28889.
[16]. Harrison, C., & Donnelly, I. A. (2011). A theory of smart cities. Proceedings of the 55th Annual Meeting of the ISSS – 2011, Hull, UK.
[17]. Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2016). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98-115.
[18]. Ikegwu, A.C., Nweke, H.F., Mkpojiogu, E. et al. Recently emerging trends in big data analytic methods for modeling and combating climate change effects. Energy Inform 7, 6 (2024). https://doi.org/10.1186/s42162-024-00307-5
[19]. Jadhao, O., Pawar, H., Somkuwar, V., Dongre, O., Bhagwatkar, C., & Bode, K. (2023). Advance City Surveillance Using Data Analysis. International Journal for Research in Applied Science and Engineering Technology, 11(4), 1290–1294. https://doi.org/10.22214/ijraset.2023.50299
[20]. Kamrowska-Załuska, D. (2021). Impact of AI- Based Tools and Urban Big Data Analytics on the Design and Planning of Cities. Land, 10(11), 1209. https://doi.org/10.3390/land10111209
[21]. Kitchin, R. (2014). The data revolution: Big data, open data, data infrastructures and their consequences. SAGE Publications.
[22]. Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J., Ogata, H., . . . Tsai, C. C. (2020). Challenges and Future Directions of Big Data and Artificial Intelligence in Education. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.580820
[23]. Nam, T., & Pardo, T. A. (2011). Conceptualizing smart city with dimensions of technology, people, and institutions. Proceedings of the 12th Annual International Conference on Digital Government Research, 282-291.
[24]. Pardo, T. A., Nam, T., & Kim, T. (2011). Conceptualizing smart city with dimensions of technology, people, and institutions. Proceedings of the 12th Annual International Conference on Digital Government Research, 282-291.
[25]. Role of Big Data in Smart Cities and IoT Implementations. (n.d.). Retrieved from https://www.trigyn.com/insights/role-big- data-smart-cities-and-iot-implementations
[26]. Shi, W., Goodchild, M., Batty, M., Li, Q., Liu, X., & Zhang, A. (2022). Prospective for urban informatics. Urban Informatics, 1(1). https://doi.org/10.1007/s44212-022-00006-0
[27]. Son, T. H., Weedon, Z., Yigitcanlar, T., Sanchez, T., Corchado, J. M., & Mehmood, R. (2023). Algorithmic urban planning for smart and sustainable development: Systematic review of the literature. Sustainable Cities and Society, 94, 104562. https://doi.org/10.1016/j.scs.2023.104562
[28]. UN-Habitat. (2016). World Cities Report 2016: Urbanization and Development – Emerging Futures. United Nations Human Settlements Programme.
[29]. United Nations. (2018). World Urbanization Prospects: The 2018 Revision. United Nations Department of Economic and Social Affairs.
[30]. Wang, Y. (2023). Big Data Applications for Smart Cities. Journal of Innovation and Development, 5(3), 1–4. https://doi.org/10.54097/mj1gj9u9