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• W2908096145 abstract "A decentralized detection method is proposed for revealing a radioactive nuclear source with unknown intensity and at unknown location, using a number of cheap radiation counters, to ensure public safety in smart cities. In the source present case, sensors nodes record an (unknown) emitted Poisson-distributed radiation count with a rate decreasing with the sensor-source distance (which is unknown), buried in a known Poisson background and Gaussian measurement noise. To model energy-constrained operations usually encountered in an Internet of Things (IoT) scenario, local one-bit quantizations are made at each sensor over a period of time. The sensor bits are collected via error-prone binary symmetric channels by the Fusion Center (FC), which has the task of achieving a better global inference. The considered model leads to a one-sided test with parameters of nuisance (i.e., the source position) observable solely in the case of $$mathcal {H}_{1}$$ hypothesis. Aiming at reducing the higher complexity requirements induced by the generalized likelihood ratio test, Davies’ framework is exploited to design a generalized form of the locally optimum detection test and an optimization of sensor thresholds (resorting to a heuristic principle) is proposed. Simulation results verify the proposed approach." @default.
• W2908096145 created "2019-01-11" @default.
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• W2908096145 date "2019-01-01" @default.
• W2908096145 modified "2023-10-18" @default.
• W2908096145 title "IoT-Enabled Distributed Detection of a Nuclear Radioactive Source via Generalized Score Tests" @default.
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• W2908096145 doi "https://doi.org/10.1007/978-981-13-5758-9_7" @default.
• W2908096145 hasPublicationYear "2019" @default.
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