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通过无线传感器网络和光纤传感器进行车辆检测。

Vehicles detection through wireless sensors networks and optical fiber sensors.

作者信息

Khlaifi Hacen, Zrelli Amira, Ezzedine Tahar

机构信息

Communications System Laboratory, University of Tunis El-Manar, Tunis, Tunisia.

Faculty of Sciences of Gabes, University of Gabès, Gabès, Tunisia.

出版信息

Sci Rep. 2025 Jul 25;15(1):27121. doi: 10.1038/s41598-025-09033-8.

Abstract

Due to the evolving variations in government and political systems both domestically and internationally, along with the imposition of high tariffs at borders, these borders have become vulnerable points for terrorism and smuggling activities. Consequently, each country endeavors to develop its own protection systems, with the technologies employed varying depending on the severity and significance of the installations to be safeguarded. While some of these technologies are costly and redundant, others offer effective and adaptable levels of efficiency. Therefore, designing a surveillance system capable of monitoring and controlling access has become essential. In this context, the present work holds significant strategic and geopolitical importance. It integrates established alarm and monitoring methods with innovative Internet of Things (IoT) applications, including Wireless Sensor Networks (WSN) and Optical Fiber Sensors (OFS). This article introduces the deployment of wireless radar nodes in conjunction with Bragg fiber sensors to identify each approaching intruding vehicle in the monitored zone, enabling the determination of its speed, weight, and wheelbase distance. Our system's results demonstrated acceptable levels of intruder detection and classification. We verify that the wavelength-based pressure detection error rate is small, approximately 0.05 kg/cm2. The wheelbase distance estimate had an error rate of around 0.012 m, while the weight calculation from the pressure had an error rate of about 12 kg. This value is negligible and cannot skew the outcome. In our case, we apply WSN, radar and optical fiber sensors to detect vehicles in the border area. However, several works in literature.

摘要

由于国内外政府和政治体制不断演变,加上边境实施高额关税,这些边境已成为恐怖主义和走私活动的薄弱点。因此,每个国家都努力开发自己的保护系统,所采用的技术因要保护设施的严重性和重要性而异。虽然其中一些技术成本高昂且冗余,但其他技术提供了有效且适应性强的效率水平。因此,设计一个能够监测和控制出入的监视系统变得至关重要。在这种背景下,本工作具有重大的战略和地缘政治意义。它将既定的警报和监测方法与创新的物联网(IoT)应用相结合,包括无线传感器网络(WSN)和光纤传感器(OFS)。本文介绍了结合布拉格光纤传感器部署无线雷达节点,以识别监测区域内每辆接近的入侵车辆,从而能够确定其速度、重量和轴距距离。我们系统的结果表明入侵检测和分类达到了可接受的水平。我们验证基于波长的压力检测错误率很小,约为0.05 kg/cm²。轴距距离估计的错误率约为0.012 m,而根据压力计算重量的错误率约为12 kg。这个值可以忽略不计,不会影响结果。在我们的案例中,我们应用无线传感器网络、雷达和光纤传感器来检测边境地区的车辆。然而,文献中有几项研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f8f/12297390/21968c1365ef/41598_2025_9033_Fig1_HTML.jpg

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