A Sentinel Node for Event-Driven Structural Monitoring of Road Bridges Using Wireless Sensor Networks

Abstract

Event-driven monitoring policies enable to significantly reduce the power consumption of wireless sensor networks by reducing the recording period to those time intervals that provide valuable data. The resulting longer operation lifetime increase discloses fields of application that require long monitoring periods. This paper presents a structural monitoring system that uses specialized sentinel nodes for detecting possibly heavy road vehicles and for alarming monitoring nodes, which are specialized on strain sensing. Heavy vehicles are identified by estimating nearly in real time height and length of vehicles of a traffic flow by processing data recorded from low-cost ultrasonic and magnetic displacement sensors. Field tests demonstrated that while height detection is very reliable, length detection is too imprecise to discriminate with high success rates between trucks and delivery vans.

Wireless Sensor Placement Optimization for Bridge Health Monitoring: A Critical Review

“…Figure 8 illustrates a schematic representation of magnetostrictive sensors. Moreover, magnetic sensors can be utilized to monitor and classify the length of vehicles traversing a bridge, offering timely alerts in instances of excessive heavy vehicle presence within the traffic flow [3].…”

“…Figure 9 displays an example of magnetic sensor signals. Furthermore, these sensors have been utilized for monitoring strains induced by vibrations resulting from train passage over bridges and for issuing prompt alerts in emergency scenarios where strains surpass predefined thresholds [3,5].…”

“…By employing wireless sensor nodes to monitor modal parameters such as natural frequency, damping, and vibration patterns, the condition of bridges can be assessed [1,2]. Furthermore, these networks can discern passing vehicle characteristics to provide early warnings regarding traffic flow [3], thereby offering comprehensive monitoring of bridge health from multiple perspectives.…”

“…Consequently, acceleration sensors have emerged as one of the most prevalent sensor types in the realm of structural health monitoring for bridges, finding application in simply supported girder bridges [5], arch bridges [6], cable-stayed bridges [7], and suspension bridges [8]. In addition to acceleration sensors, strain sensors, magnetic sensors, ultrasonic sensors, piezoelectric sensors, and specialized WSNs integrated with GPS are employed in bridge projects owing to their respective advantages [3,9,10]. Regarding wireless sensor hardware, current research endeavors focus on enhancing measurement accuracy [7,11], reducing node energy consumption [12], lowering sensor costs [1,10], and minimizing sensor dimensions [13].…”

Event-driven temporal models for explanations - ETeMoX: explaining reinforcement learning

“…It allows for autonomous recovery and failure prevention to guarantee long-term QoS of cloud systems. Other event-driven monitoring approaches integrate Wireless Sensor Networks (WSNs) with sentinel nodes [22,53] to detect heavy road vehicles as well as raising alarms in monitoring nodes. CEP has been widely used for real-time event-driven monitoring [3,48].…”