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<p>Recent advancements in object tracking and detection algorithms within video surveillance systems have significantly enhanced their ability to identify potential threats and anomalous activities. Addressing sustainability and efficiency challenges, this research introduces a novel (You only look once) YOLOv9-based object recognition model for a remotely operated surveillance rover. By optimizing the detection algorithm using TensorRT, the system achieves a remarkable 93.27% accuracy when trained on the Indian Driving Dataset (IDD), reducing image processing time by 20% and network latency by 15%. The proposed system integrates a hybrid solar-battery configuration, enabling energy-efficient operation across diverse surveillance scenarios. Utilizing High Efficiency Video Coding (HEVC) compression, the rover ensures seamless video transmission while maintaining high visual quality. A user-friendly web interface provides global remote control and lives streaming capabilities, demonstrating the system’s adaptability in real-time object detection applications for augmented reality, robotics, autonomous vehicles, and surveillance systems.</p>

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A novel and optimized YOLO model for H.265 encoded video frames

  • 期刊论文

  • 发表日期：

    2025年5月22日

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  • Balaji Ganesh Rajagopal,
  • R. Jagadeesh Kannan,
  • R. Deebalakshmi,
  • R. R. Dharun Raagav

摘要

Recent advancements in object tracking and detection algorithms within video surveillance systems have significantly enhanced their ability to identify potential threats and anomalous activities. Addressing sustainability and efficiency challenges, this research introduces a novel (You only look once) YOLOv9-based object recognition model for a remotely operated surveillance rover. By optimizing the detection algorithm using TensorRT, the system achieves a remarkable 93.27% accuracy when trained on the Indian Driving Dataset (IDD), reducing image processing time by 20% and network latency by 15%. The proposed system integrates a hybrid solar-battery configuration, enabling energy-efficient operation across diverse surveillance scenarios. Utilizing High Efficiency Video Coding (HEVC) compression, the rover ensures seamless video transmission while maintaining high visual quality. A user-friendly web interface provides global remote control and lives streaming capabilities, demonstrating the system’s adaptability in real-time object detection applications for augmented reality, robotics, autonomous vehicles, and surveillance systems.