Theses Doctoral

Multisensory Smartphone Applications in Vibration-Based Structural Health Monitoring

Ozer, Ekin

Advances in sensor technology and computer science in the last three decades have boosted the importance of system identification and vibration-based structural health monitoring (SHM) in civil infrastructure safety and integrity assessment. On the other hand, practical and financial issues in system instrumentation, maintenance, and operation have remained as fundamental problems obstructing the widespread use of SHM applications. For this reason, to reduce system costs and improve practicality as well as sustainability, researchers have been working on emerging methods such as wireless, distributed, mobile, remote, smart, multisensory, and heterogeneous sensing systems.
Smartphones with built-in batteries, processor units, and a variety of sensors, have stood as a promising hardware and software environment that can be used as SHM components. Communication capabilities with the web, enable them to compose a smart and participatory sensor network of outnumbered individuals. Besides, crowdsourcing power offered by citizens, sets a decentralized and self-governing SHM framework which can even be pertained by very limited equipment and labor resources.
Yet, citizen engagement in an SHM framework brings numerous challenges as well as opportunities. In a citizen-induced SHM scenario, the system administrators have limited or no control over the sensor instrumentation and the operation schedule, and the acquired data is subjected change depending on the measurement conditions. The citizen-induced errors can stem from spatial, temporal, and directional uncertainties since the sensor configuration relies on smartphone users’ decisions and actions. Moreover, the sensor-structure coupling may be unavailable where the smartphone is carried by the user, and as a consequence, the vibration features measured by smartphones can be modified due to the human biomechanical system. In addition, in contrast with the conventional high fidelity sensors, smartphone sensors are of limited quality and are subjected to high noise levels.
This dissertation utilizes multisensory smartphone features to solve citizen-induced uncertainties and develops a smartphone-based SHM methodology which enables a cyber-physical system through mobile crowdsourcing. Using smartphone computational and communicational power, combined with a variety of embedded sensors such as accelerometer, gyroscope, magnetometer and camera, spatiotemporal and biomechanical citizen-induced uncertainties can be eliminated from the crowdsourced smartphone data, and eventually, structural vibrations collected from numerous buildings and bridges can be collected on a single cloud server. Therefore, unlike the conventional platforms designed and implemented for a particular structure, citizen-engaged and smartphone-based SHM can serve as intelligent, scalable, fully autonomous, cost-free, and durable cyber-physical systems drastically changing the forthcoming trends in civil infrastructure monitoring.

In this dissertation, iOS is used as the application development platform to produce a smartphone-based SHM prototype, namely Citizen Sensors for SHM. In addition, a web-based software is developed and cloud services are implemented to connect individual smartphones to an administrator base and automate data submission and processing procedure accordingly. Finally, solutions to citizen-induced problems are provided through numerous laboratory and field test applications to prove the feasibility of smartphone-based SHM with real life examples. Through collaborative use of the software, principles and methodologies presented in this dissertation, smartphones can be the core component of futuristic smart, resilient, and sustainable city and infrastructure systems. And this study lays down an innovative and integrated foundation empowering citizens to achieve these goals.


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More About This Work

Academic Units
Civil Engineering and Engineering Mechanics
Thesis Advisors
Feng, Maria Q.
Ph.D., Columbia University
Published Here
October 12, 2016