Paper
10 April 2007 Insurance derivatives based on information obtained by sensor networks to improve the safety of buildings and urban systems
Author Affiliations +
Abstract
Despite the modernity of today's cities, all kinds of buildings are built without proper hedge strategies against the risk of large disasters such as earthquakes. In order to control such risks, new engineering and economic mechanisms should be developed. On the engineering front recently Structural Health Monitoring (SHM) systems using sensor networks have been proposed and even enacted in many variations. Fortunately, data taken from such systems serve as good candidates as risk indices for each building. The purpose of this study is to propose insurance derivatives to maintain and improve the safety of buildings and to provide a risk hedge instrument for owners. These derivatives should be able to take advantage of information gained from SHM sensor networks. In this study, hazard information offered by J-SHIS (Japanese Seismic Hazard Information Station), and Weibull distributions associated with Is-WF (Seismic index based on seismic diagnosis), proposed by Okada and Takai as Damage Index Functions, were used for the quantification of risk. This simply defined quantification was used to evaluate the proposed earthquake derivatives. Results showed that the proposed derivative is better than the functions currently used for earthquake insurance, and that it has potential to be used as incentive for seismic strengthening.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hitoshi Tamura and Akira Mita "Insurance derivatives based on information obtained by sensor networks to improve the safety of buildings and urban systems", Proc. SPIE 6529, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2007, 65292L (10 April 2007); https://doi.org/10.1117/12.715550
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KEYWORDS
Earthquakes

Buildings

Sensor networks

Structural health monitoring

Safety

Structural engineering

Systems engineering

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