Video Surveillance Processing Algorithms utilizing Artificial Intelligent (AI) for Unmanned Autonomous Vehicles (UAVs).
Video Surveillance Processing Algorithms utilizing Artificial Intelligent (AI) for Unmanned Autonomous Vehicles (UAVs).
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作者：
Nguyen MT;Truong LH;Le TTH
开发的解决方案可以显着减少数据传输。该解决方案可以通过摄像头监控实现智能制造。仿真结果验证了该方法的实际可行性。随着科学技术的进步，无人机（无人机）和摄像头监控系统（CSS）的结合是目前安全和监控操作相关实际应用的一种很有前途的解决方案。然而，UAV-CSS最大的风险和挑战之一是分析，处理和传输数据，特别是计算能力，存储和传输带宽过载的限制。传统的数据采集方法主要是对无人机采集到的数据进行处理和传输，需要耗费大量的能量。一定量的数据是冗余的，不需要处理或传输。本文提出了一种有效的算法来优化无人机CSS系统中的数据传输和接收，基于人工智能（AI）的数据处理平台。该算法创建一个初始背景帧，并更新为发送到服务器的完整背景。它分割场景中的感兴趣区域（移动对象），然后仅发送更改。这支持CSS显著减少数据存储或数据传输。此外，系统的复杂性可以大大降低。该算法的主要贡献可以列举如下：实验方法结果表明，减少高达80%的存储容量和传输数据。
The developed solution can reduce data transmission significantly. The solution can empower smart manufacturing via camera surveillance. Simulation results have validated practical viability of this approach. With the advancement of science and technology, the combination of the unmanned aerial vehicle (UAV) and camera surveillance systems (CSS) is currently a promising solution for practical applications related to security and surveillance operations. However, one of the biggest risks and challenges for the UAV-CSS is analysis, process, and transmission data, especially, the limitations of computational capacity, storage and overloading the transmission bandwidth. Regard to conventional methods, almost the data collected from UAVs is processed and transmitted that cost huge energy. A certain amount of data is redundant and not necessary to be processed or transmitted. This paper proposes an efficient algorithm to optimize the transmission and reception of data in UAV-CSS systems, based on the platforms of artificial intelligence (AI) for data processing. The algorithm creates an initial background frame and update to the complete background which is sent to server. It splits the region of interest (moving objects) in the scene and then sends only the changes. This supports the CSS to reduce significantly either data storage or data transmission. In addition, the complexity of the systems could be significantly reduced. The main contributions of the algorithm can be listed as follows;The experimental method results show that reducing up to 80% of storage capacity and transmission data.
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