Structural Health Monitoring Using Wireless IoT Sensors

Abstract

Structural Health Monitoring (SHM) has become an important science to help keep civil infrastructure like bridges, buildings, dams, and industrial plants safe, reliable and lasting. Traditional methods of SHM have depended primarily on wired sensor networks and periodic manual inspections that are regularly expensive, labor-intensive and lack real-time responsiveness. The present-day breakthroughs in Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) have made it possible to create intelligent, scalable, and energy-efficient SHM systems that would allow continuous monitoring and remote diagnostics. This paper provides an extensive exploration of Structural Health Monitoring with wireless IoT sensors in terms of system architecture, sensing modalities, communication protocols, data processing methods, and damage detection methods. The intricate literature survey reveals the development of the SHM technologies and outlines the gaps in the research. The suggested methodology will combine low-power wireless sensors, edge computing, and cloud-based analytics to track such structural parameters as strain, vibration, displacement, and temperature. Damage detection and feature extraction mathematical models are discussed and the experimental validation strategies. The findings support the idea that IoT-based SHM systems can greatly improve the accuracy of fault detection, decrease the cost of maintenance, and predictive maintenance. The paper has reached the conclusion that wireless IoT-based SHM is an innovative solution to smart infrastructure management and offers the research perspectives on its future development in terms of scalability and artificial intelligence incorporation.