xImpact: Intelligent Wireless System for Cost-Effective Rapid Condition Assessment of Bridges under Impacts.

Bridge strikes by over-height vehicles or ships are critical sudden events. Due to their unpredictable nature, many events go unnoticed or unreported, but they can induce structural failures or hidden damage that accelerates the bridge's long-term degradation. Therefore, always-on monitoring is essential for deployed systems to enhance bridge safety through the reliable detection of such events and the rapid assessment of bridge conditions. Traditional bridge monitoring systems using wired sensors are too expensive for widespread implementation, mainly due to their significant installation cost. In this paper, an intelligent wireless monitoring system is developed as a cost-effective solution. It employs ultralow-power, event-triggered wireless sensor prototypes, which enables on-demand, high-fidelity sensing without missing unpredictable impact events. Furthermore, the proposed system adopts a smart artificial intelligence (AI)-based framework for rapid bridge assessment by utilizing artificial neural networks. Specifically, it can identify the impact location and estimate the peak force and impulse of impacts. The obtained impact information is used to provide early estimation of bridge conditions, allowing the bridge engineers to prioritize resource allocation for the timely inspection of the more severe impacts. The performance of the proposed monitoring system is demonstrated through a full-scale field test. The test results show that the developed system can capture the onset of bridge impacts, provide high-quality synchronized data, and offer a rapid damage assessment of bridges under impact events, achieving the error of around 2 m in impact localization, 1 kN for peak force estimation, and 0.01 kN·s for impulse estimation. Long-term deployment is planned in the future to demonstrate its reliability for real-life impact events.

Natural soundscapes of lowland river habitats and the potential threat of urban noise pollution to migratory fish.

Migratory fish populations have experienced great declines, and considerable effort have been put into reducing stressors, such as chemical pollution and physical barriers. However, the importance of natural sounds as an information source and potential problems caused by noise pollution remain largely unexplored. The spatial distribution of sound sources and variation in propagation characteristics could provide migratory fish with acoustic cues about habitat suitability, predator presence, food availability and conspecific presence. We here investigated the relationship between natural soundscapes and local river conditions and we explored the presence of human-related sounds in these natural soundscapes. We found that 1a) natural river sound profiles vary with river scale and cross-sectional position, and that 1b) depth, width, water velocity, and distance from shore were all significant factors in explaining local soundscape variation. We also found 2a) audible human activities in almost all our underwater recordings and urban and suburban river parts had elevated sound levels relative to rural river parts. Furthermore, 2b) daytime levels were louder than night time sound levels, and bridges and nearby road traffic were much more prominent with diurnal and weekly patterns of anthropogenic noise in the river systems. We believe our data show high potential for natural soundscapes of low-land river habitat to serve as important environmental cues to migratory fish. However, anthropogenic noise may be particularly problematic due to the omnipresence, and relatively loud levels relative to the modest dynamic range of the natural sound sources, in these slow-flowing freshwater systems.