Browsing by Author "Tong, Xinlong"

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    The Development and Field Evaluation of an IoT System of Low-Power Vibration for Bridge Health Monitoring
    Tong, Xinlong; Yang, Hailu; Wang, Linbing; Miao, Yinghao (MDPI, 2019-03-11)
    Bridge safety is important for the safety of vehicles and pedestrians. This paper presents a study on the development of a low-power wireless acceleration sensor and deployment of the sensors on a wireless gateway and cloud platform following the Internet of Things (IoT) protocols for bridge monitoring. The entire system was validated in a field test on the Chijing bridge in Shanghai. Field evaluations indicated that the developed IoT bridge monitoring system could achieve the functions of real-time data acquisition, transmission, storage and analytical processing to synthesize safety information of the bridge. The demonstrated system was promising as a complete, practical, readily available, low-cost IoT system for bridge health monitoring.
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    A Preliminary Study on the IoT-Based Pavement Monitoring Platform Based on the Piezoelectric-Cantilever-Beam Powered Sensor
    Hou, Yue; Wang, Linbing; Wang, Dawei; Yang, Hailu; Guo, Meng; Ye, Zhoujing; Tong, Xinlong (Hindawi, 2017-06-07)
    Green and sustainable power supply for sensors in pavement monitoring system has attracted attentions of civil engineers recently. In this paper, the piezoelectric energy harvesting technology is used to provide the power for the acceleration sensor and Radio Frequency (RF) communication. The developed piezoelectric bimorph cantilever beam is used for collecting the vibrational energy. The energy collection circuit is used to charge the battery, where the power can achieve 1.68 mW and can meet the power need of acceleration sensor for data collection and transmission in one operation cycle, that is, 32.8 seconds. Based on the piezoelectric-cantilever-beam powered sensor, the preliminary study on the IoT-based pavement monitoring platform is suggested, which provides a new applicable approach for civil infrastructure health monitoring.