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Drones or unmanned aerial vehicles (UAVs) are gradually taking important positions in various sectors like surveillance, logistics, and public safety. Their ability has enormously evolved with the application of artificial intelligence (AI). This paper examines two major innovations first in how AI algorithms like YOLOv8 and multi-object tracking (MOT) enable real-time multiple moving objects tracking and secondly, AI can support the autonomous navigation and task execution in drones. Finally, the paper discusses the challenges these drones pose in dynamic environments in terms of risk to privacy and regulation due to their increasing autonomy. The utilization of AI-based tracking and control makes it one of the vital tools for various commercial fields and applications in public safety.

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UAV Technology for Multi-object Tracking and the YOLOV8 Algorithm: A Review

  • 会议论文

  • 发表日期：

    2026年

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  • P. Monica,
  • Farooque Azam,
  • Dakshish Abrol

摘要

Drones or unmanned aerial vehicles (UAVs) are gradually taking important positions in various sectors like surveillance, logistics, and public safety. Their ability has enormously evolved with the application of artificial intelligence (AI). This paper examines two major innovations first in how AI algorithms like YOLOv8 and multi-object tracking (MOT) enable real-time multiple moving objects tracking and secondly, AI can support the autonomous navigation and task execution in drones. Finally, the paper discusses the challenges these drones pose in dynamic environments in terms of risk to privacy and regulation due to their increasing autonomy. The utilization of AI-based tracking and control makes it one of the vital tools for various commercial fields and applications in public safety.