A Battery-free Pavement Roughness Estimation System Based on Kinetic Energy Harvesting

doi:10.1109/ISCAS48785.2022.9937719

	A Battery-free Pavement Roughness Estimation System Based on Kinetic Energy Harvesting
	Hailiang Yang; Li Teng; Junrui Liang
	2022
会议录名称	2022 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS)
ISSN	0271-4302
发表状态	已发表
DOI	10.1109/ISCAS48785.2022.9937719
摘要	Wireless sensor network (WSN) enables the continuous monitoring of environmental conditions. These systems are usually powered by batteries. Given that there might be tremendous distributed sensor nodes in a network, battery maintenance must become one of the major challenges for their massive deployment. Energy harvesting technology, by which energy is extracted from the ambient environment, is developed for powering the ubiquitous Internet of Things (IoT) devices using different types of local energy, such as solar, vibration, and wind. In this paper, based on the vibration energy harvesting technology, we introduce a battery-free pavement roughness estimation system (BF-PRES), which provides road roughness information by linking the driving vibration and wireless packet count. Instead of harvesting energy to power an off-the-shelf commercial accelerometer and implementing some algorithms for vibration estimation, BF-PRES simply sends out a BLE Beacon packet, when the accumulated energy arrives at a sufficient level. Given that larger vibration intensity gives higher harvested power, the packet count within a constant time interval should be positively related to the road roughness. Lab testing shows the feasibility of the proposed design. In addition, this study also provides a new design scheme and easy implementation of battery-free or energy-constrained IoT systems.
关键词	Vibrations Wireless communication Wireless sensor networks Transmitters Roads Estimation Batteries
会议地点	Austin, TX, USA
会议日期	27 May-1 June 2022
URL	查看原文
收录类别	EI
来源库	IEEE
引用统计	正在获取...
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/248899
专题	信息科学与技术学院_硕士生信息科学与技术学院_PI研究组_梁俊睿组信息科学与技术学院_博士生
作者单位	School of Information Science and Technology, ShanghaiTech University, Shanghai, China
第一作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Hailiang Yang,Li Teng,Junrui Liang. A Battery-free Pavement Roughness Estimation System Based on Kinetic Energy Harvesting[C],2022.