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Toward Optimum Topology Protocol in Health Monitoring

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Performability in Internet of Things

Abstract

Sensor technology has opened up numerous opportunities to advanced health and maintenance monitoring of civil infrastructure. Compared to the traditional tactics, it offers a better way of providing relevant information regarding the condition of building structure at a lower price and greater range. This paper addresses the coverage area and lifetime-related issues arise in the building structural monitoring system. The monitoring system consists of a large number of sensor nodes for collecting structural health information. Numerous domestic buildings, especially long-span buildings, have lower frequency response that is challenging to accurately measure using a number of deployed sensor nodes. The way the sensor nodes are connected plays an important role in providing signals with required strengths. Out of many topologies, the dense and sparse topology was extensively used in sensor network applications for collecting health information. The lifetime of the wireless sensor network is a fundamental issue because it determines the whole system aliveness. Network lifetime is one of the most important performance indicators for real-life application. The objective of this article is to investigate the network lifetime and compare the computational results of different kinds of transmission construction protocols to find the optimum lifetime protocol for extending the monitoring system lifetime. The proposed dense topology sensor network maximizes the network lifetime and minimizes the system cost. The result shows that the dense topology would be a good choice for monitoring building structural health damage.

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Acknowledgments

The research described in this paper was partially financially supported by the Science Fund Malaysia.

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Haque, M.E., Hannan, M.A. (2019). Toward Optimum Topology Protocol in Health Monitoring. In: Al-Turjman, F. (eds) Performability in Internet of Things. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-93557-7_6

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  • DOI: https://doi.org/10.1007/978-3-319-93557-7_6

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