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Video Surveillance Processing Algorithms utilizing Artificial Intelligent (AI) for Unmanned Autonomous Vehicles
Minh T Nguyen1, Linh H Truong2, Trang T H Le1
1Thai Nguyen University of Technology, Viet Nam.
Methodsx
|August 26, 2021
Summary
This study introduces an AI-driven algorithm for Unmanned Aerial Vehicle (UAV) and Camera Surveillance Systems (CSS) to optimize data transmission. The method significantly reduces data storage and transmission, enhancing efficiency for surveillance operations.
Area of Science:
- Computer Science
- Artificial Intelligence
- Engineering
Background:
- Unmanned Aerial Vehicle (UAV) and Camera Surveillance Systems (CSS) integration offers advanced security solutions.
- Challenges include data processing, storage limitations, and transmission bandwidth overload in UAV-CSS.
- Conventional methods incur high energy costs due to extensive data processing and transmission.
Purpose of the Study:
- To propose an efficient algorithm for optimizing data transmission and reception in UAV-CSS.
- To leverage artificial intelligence (AI) for intelligent data processing within UAV-CSS.
- To reduce the computational complexity and energy consumption of UAV-CSS operations.
Main Methods:
- Developed an AI-based algorithm for efficient data management in UAV-CSS.
- Implemented background frame creation and updates for efficient data transmission.
- Utilized region of interest (ROI) segmentation to transmit only changes (moving objects).
Main Results:
- Achieved significant reductions in data transmission requirements.
- Demonstrated up to an 80% decrease in data storage and transmission capacity.
- Validated the practical viability and efficiency of the proposed approach through simulations.
Conclusions:
- The AI-driven algorithm effectively optimizes data handling in UAV-CSS.
- The solution offers substantial improvements in storage and transmission efficiency.
- This approach supports the advancement of smart manufacturing through enhanced camera surveillance capabilities.
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