Rashid Ahmad1, Asif Nawaz1,*, Ghulam Mustafa1, Tariq Ali1, Mehdi Tlija2, Mohammed A. El-Meligy3,4, Zohair Ahmed5
CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4171-4194, 2024, DOI:10.32604/cmc.2024.056971
- 19 December 2024
Abstract Crime hotspot detection is essential for law enforcement agencies to allocate resources effectively, predict potential criminal activities, and ensure public safety. Traditional methods of crime analysis often rely on manual, time-consuming processes that may overlook intricate patterns and correlations within the data. While some existing machine learning models have improved the efficiency and accuracy of crime prediction, they often face limitations such as overfitting, imbalanced datasets, and inadequate handling of spatiotemporal dynamics. This research proposes an advanced machine learning framework, CHART (Crime Hotspot Analysis and Real-time Tracking), designed to overcome these challenges. The proposed methodology… More >
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