Abstract
Civil infrastructure systems such as bridges and buildings are expensive and safety-critical assets of our society. As they are deteriorating with time, it is of crucial importance to monitor their condition and provide timely alarms. Traditional systems to monitor structural condition generally leverage cables to deliver the collected data from sensor nodes to a central processing station, suffering from high cost, long deployment time, and delays in processing. Recently emerged systems using wireless sensor networks (WSNs) have started to gain more and more attention due to their low cost and ease of deployment. However, due to bandwidth limitation and demand on in-network processing, designing distributed versions of structural health monitoring (SHM) algorithms and implementing them within a WSN is a challenging and necessary task.This chapter mainly focuses on designing and implementing effective and energy-efficient SHM algorithms in resource-limited WSNs. We first give a review of the related works. Then we choose modal analysis, a classic algorithm widely adopted in civil engineering, as an example to show how this technique can be embedded within a WSN. At last, we propose a WSN-Cloud architecture which we believe is a promising paradigm for the future SHM system.
Original language | English |
---|---|
Title of host publication | Big Data Analytics for Sensor-Network Collected Intelligence |
Publisher | Elsevier Inc. |
Pages | 241-255 |
Number of pages | 15 |
ISBN (Electronic) | 9780128096253 |
ISBN (Print) | 9780128093931 |
DOIs | |
Publication status | Published - 8 Feb 2017 |
Keywords
- Building safety monitoring
- Smart structures
- Structural health monitoring
- Wireless sensor networks
ASJC Scopus subject areas
- General Computer Science