Department of Engineering Technology (INDI), Vrije Universiteit Brussel (VUB), 1050 Brussels, Belgium.
Department of Information Engineering, San Pablo-CEU University, 28668 Madrid, Spain.
Sensors (Basel). 2020 Dec 29;21(1):158. doi: 10.3390/s21010158.
Traffic congestion is, on a daily basis, responsible for a significant amount of economic and social costs. One of the critical examples is the obstruction of priority vehicles during fast trajectories, which potentially costs lives and property in case of delay that is too great. By means of visual sensing methods, solutions and schedules have already been proposed for adjusting traffic light sequences depending on a priority vehicle's position. However, these mechanisms are computation and power intensive. Deploying and powering a large-scale network will have a crucial economical cost. Furthermore, these devices will not always have access to sufficient power. To provide a solution, we developed an acoustic and self-powered device that can detect priority vehicles and can be cost effectively deployed to define a sensor network. The device combines the detection of priority vehicles and the harvesting of sound energy through triboelectrification. This paper will introduce the use of triboelectric energy harvesting, specifically in a self-powered wireless sensor network for priority vehicle detection. Furthermore, it shows how to increase the power performance of such a generator. Finally, the results are analyzed.
交通拥堵每天都会造成大量的经济和社会成本。其中一个关键的例子是在快速行驶的过程中阻塞优先车辆,这可能会导致生命和财产的损失,如果延误时间过长的话。通过视觉传感方法,已经提出了根据优先车辆的位置来调整交通信号灯序列的解决方案和时间表。然而,这些机制在计算和功耗方面都很密集。部署和为大规模网络供电将带来关键的经济成本。此外,这些设备并不总是能够获得足够的电力。为了解决这个问题,我们开发了一种声学和自供电的设备,可以检测优先车辆,并可以以具有成本效益的方式进行部署,以定义传感器网络。该设备通过摩擦起电结合了优先车辆的检测和声音能量的收集。本文将介绍摩擦起电能量收集的使用,特别是在用于优先车辆检测的自供电无线传感器网络中。此外,还展示了如何提高这种发电机的功率性能。最后,对结果进行了分析。