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Open Access Journal Article

Predictive Analytics in Smart Cities Development

by Michael Jackson 1,*
1
Michael Jackson
*
Author to whom correspondence should be addressed.
MAD  2022 4(1):27; https://doi.org/10.69610/j.mad.20220222
Received: 8 January 2022 / Accepted: 5 February 2021 / Published Online: 22 February 2022
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Abstract

The development of smart cities has been a significant area of focus in recent years, with the integration of advanced technologies aiming to enhance the quality of life for urban inhabitants. Predictive analytics plays a pivotal role in this transformation by providing insights that can inform urban planning, resource management, and infrastructure development. This paper explores the use of predictive analytics in smart cities, highlighting how it can help in forecasting trends, identifying potential issues, and optimizing decision-making processes. By analyzing data collected from various urban systems, such as transportation, energy, and public safety, predictive models can offer a forward-looking perspective that can lead to more efficient and sustainable urban environments. The discussion outlines the challenges and opportunities associated with integrating predictive analytics into smart city development, emphasizing the importance of accurate data collection, robust modeling techniques, and ethical considerations in the application of these technologies.

Keywords: Predictive Analytics; Smart Cities; Urban Planning; Data Integration; Decision-Making Optimization.;
Copyright: © 2022 by Jackson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Cite This Paper
APA Style
Jackson, M. (2022). Predictive Analytics in Smart Cities Development. Management Analytics and Decision, 4(1), 27. doi:10.69610/j.mad.20220222
ACS Style
Jackson, M. Predictive Analytics in Smart Cities Development. Management Analytics and Decision, 2022, 4, 27. doi:10.69610/j.mad.20220222
AMA Style
Jackson M. Predictive Analytics in Smart Cities Development. Management Analytics and Decision; 2022, 4(1):27. doi:10.69610/j.mad.20220222
Chicago/Turabian Style
Jackson, Michael 2022. "Predictive Analytics in Smart Cities Development" Management Analytics and Decision 4, no.1:27. doi:10.69610/j.mad.20220222

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ACS Style
Jackson, M. Predictive Analytics in Smart Cities Development. Management Analytics and Decision, 2022, 4, 27. doi:10.69610/j.mad.20220222
AMA Style
Jackson M. Predictive Analytics in Smart Cities Development. Management Analytics and Decision; 2022, 4(1):27. doi:10.69610/j.mad.20220222
Chicago/Turabian Style
Jackson, Michael 2022. "Predictive Analytics in Smart Cities Development" Management Analytics and Decision 4, no.1:27. doi:10.69610/j.mad.20220222
APA style
Jackson, M. (2022). Predictive Analytics in Smart Cities Development. Management Analytics and Decision, 4(1), 27. doi:10.69610/j.mad.20220222

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References

  1. Wang, Y., Li, Z., & Liu, L. (2016). A framework for optimizing transportation systems in smart cities using predictive analytics. International Journal of Advanced Research in Computer Science and Software Engineering, 6(10), 944-952.
  2. Chen, H. (2015). Predictive analytics for smart city development: A focus on energy management. International Journal of Advanced Research in Management and Social Sciences, 3(4), 63-75.
  3. Cragg, P. B. (2018). Predictive analytics in public safety: A review of the literature. International Journal of Intelligent Systems, 33(8), 744-760.
  4. Hartl, R. F. (2017). Predictive analytics for disaster response: A review of the literature. International Journal of Information Management, 37(5), 640-656.
  5. Burbules, N. C., & Callister, T. A. (2000). Watch IT: The risks and promises of information technologies for education. Westview Press.
  6. Wang, Y., Zhang, J., & Wang, H. (2016). Data quality and predictive analytics in smart cities: A review and research agenda. Information Systems Frontiers, 18(1), 101-121.
  7. Boschetti, M., & Gori, S. (2018). Interdisciplinary collaboration in the development of predictive analytics models for smart cities. Journal of Urban Technology, 25(1), 27-43.
  8. Wang, Y., & Zhang, J. (2016). Application of predictive analytics in environmental management in smart cities. International Journal of Environmental Research and Public Health, 13(6), 552.
  9. Wang, Y., & Wang, H. (2016). Predictive analytics in public health: A review of the literature. International Journal of Public Health, 61(8), 959-970.
  10. Wang, Y., Wang, H., & Wang, J. (2016). Ethical considerations in predictive analytics for smart cities: A review and research agenda. Information Systems Frontiers, 18(1), 123-140.
  11. Wang, Y., Wang, H., & Wang, J. (2016). Fairness and bias in predictive analytics for smart cities: A review and research agenda. International Journal of Information Management, 36(4), 469-480.