Structural health monitoring using wireless smart sensor network-An overview

Structural Health Monitoring is gaining popularity in recent times because of advancements in technology and the increasing need for repair and rehabilitation. The shift from conventional wired technologies to advanced wireless technologies is also gradually increasing in the past decade. These sensor networks are economical when used for monitoring huge structures with high design life and safety requirements like highway and roadway bridges, multi-story buildings, chimneys, offshore platforms, and nuclear reactors. Smart sensors when paired along with Artificial Intelligence tools like Artificial Neural Networks, Machine Learning, Deep Learning, and its derivatives Convolutional Neural Networks, Hybrid Intelligence, Cloud Computing make the monitoring system completely automated. This paper is a comprehensive review of advances in data acquisition, processing, diagnosis, and retrieval stages of Structural Health Monitoring both academically and commercially. The review primarily focuses on the recently used wireless data acquisition system and execution of AI resources for data prediction and data diagnosis in RCC buildings and bridges. The review also indicates the lag in real-world execution of structural health monitoring technologies despite advances in academia and insists on the development of standards to gel the gap.

Automated summary

Structural Health Monitoring has gained popularity due to advancements in technology and increasing repair and rehabilitation needs. Smart sensors paired with Artificial Intelligence tools can automate monitoring systems. Despite advancements in academia, there is a lag in real-world execution, emphasizing the need for standards to bridge the gap.