Text Analysis of Smart Cities: A Big Data-based Model

Authors

  • Ahmet E. Topcu College of Engineering and Technology, American University of the Middle East, Kuwait
  • Yehia Ibrahim Alzoubi College of Business Administration American University of the Middle East, Kuwait
  • Hüsrev Abdulcelil Karacabey Department of Computer Engineering, Ankara Yildirim Beyazit University Ankara, Turkey

Keywords:

Advanced passenger information, automatic number plate recognition, call detail record, criminal activity, data security

Abstract

Traditional criminal protection approaches rely heavily on the knowledge of legal authorities’ agents. However, it is difficult for them to extrapolate their knowledge to utilize answers in real scenarios. Furthermore, the traditional approaches frequently lose their capacity to avoid problems since they take longer to respond to them. If the crime had occurred, the victims would have already suffered. As a result, it is in the best interests of legal authorities to avoid a crime from happening. We can argue that in order to prevent crime, legal authorities effectively must use data-driven techniques and real-time data analysis. This paper suggests a big data analytics model for analyzing data from various departments. In this study, we proposed using automatic number plate recognition, call detail records, and advanced passenger information data. The proposed model may help to predict potential criminal activities before they occur. Accordingly, this model may allow authorities to stop and prepare for possible criminal activities.

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Published

21.09.2023

How to Cite

Topcu, A. E. ., Alzoubi, Y. I. ., & Karacabey, H. A. . (2023). Text Analysis of Smart Cities: A Big Data-based Model. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 724–733. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3607

Issue

Vol. 11 No. 4 (2023)

Section

Research Article

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