Low-Power Wireless Sensor Networks for Long-Term Pavement Health Monitoring

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ID: 327750
2026
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Abstract
Abstract Road pavements deteriorate slowly at first and then rapidly, so damage detected early can be repaired cheaply, while damage allowed to progress until it reaches the surface demands costly rehabilitation. Conventional inspection captures surface condition but struggles to follow the internal deterioration that precedes it. Embedded low-power wireless sensor networks offer a route to continuous, long-term monitoring from within the pavement itself. This review brings together the research needed to make such systems work in practice. It examines the distress mechanisms and monitoring variables that define what must be measured; compares sensing technologies, including wired gauges, fiber-optic sensors, piezoelectric and self-powered elements, and microelectromechanical systems; and considers how sensors survive construction and service while transferring strain faithfully to the surrounding material. It then addresses the three constraints that dominate buried operation: balancing energy harvesting and storage with duty-cycled sensing; transmitting data reliably across short- and long-range wireless links with adequate time synchronization; and extracting damage signals from the strong environmental and traffic noise present in pavement data, using statistical indicators, machine learning, and on-node processing. Across these themes, the review shows that monitoring is a system-level problem in which sensing, integration, energy, communication, and interpretation are tightly coupled. It identifies long-term, full-scale field validation as the central remaining gap.
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openalex_W7211953835 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors
Journal Intelligent Transportation Infrastructure
Year 2026
DOI
10.1093/iti/liag015
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