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Design for Unmanned Aerial Vehicle Data Processing and Analysis Model for Seaport Based Surveillance in Maritime Narcotics. 'A Case Dar Es Salaam Sea Port'

Richie Felician, Eliamini A Kasembe PhD

Abstract

This study presents the design and evaluation of an Unmanned Aerial Vehicle (UAV)-based facial recognition system that utilizes a police photo archive for real-time suspect identification at maritime seaports. The system processes real-time images captured by UAVs and compares them against a curated database of 669 known suspects. A total of 2,355 UAV-captured images from Ununio and Kigamboni seaports were used to evaluate the system. The model achieved a recognition accuracy of 88.6% with a processing time of 3.7 seconds per image. Compared to manual review processes, the system demonstrated significant improvements in efficiency and effectiveness in surveillance operations. Error analysis identified key limitations related to occlusion and lighting, providing insights for future model enhancements.

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