Abstract
A distributed-sensor network (DSN) is a group of sensors connected by a communication network to a set of information processing elements. These elements process the measurements and communicate with each other to extract features. A DSN consists of many sensors that can pool their information to achieve a better overall estimate. The estimation structure consists of a central processor (or station) and two local processors. An extension of the results to the case of m local stations is straightforward. The situation in which the local measurement data at each local station are synchronised with each other may also considered. Although many techniques have been developed for the DSN system, more improved and powerful techniques are needed in areas such GPS (Global Position Systems) detection resource allocation, communication control…etc [1]
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Tzafestas, S.G., Laliotis, L.N. (1999). Current Techniques in Distributed Sensor Networks and Connection with AI and GIS: An Overview. In: Tzafestas, S.G. (eds) Advances in Intelligent Systems. International Series on Microprocessor-Based and Intelligent Systems Engineering, vol 21. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-4840-5_40
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DOI: https://doi.org/10.1007/978-94-011-4840-5_40
Publisher Name: Springer, Dordrecht
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