Optimisation in the Design of Environmental Sensor Networks with Robustness Consideration
Autor: | Greg Timms, Paul Turner, Vishv Malhotra, Setia Budi, Paulo de Souza |
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Jazyk: | angličtina |
Rok vydání: | 2015 |
Předmět: |
Computer science
optimisation Evolutionary algorithm computer.software_genre lcsh:Chemical technology Biochemistry Representativeness heuristic Article Analytical Chemistry sensor networks deployment Region of interest Robustness (computer science) Redundancy (engineering) data quality lcsh:TP1-1185 Electrical and Electronic Engineering Instrumentation sensor networks design Environmental sensor evolutionary algorithm noise detection Atomic and Molecular Physics and Optics Reliability engineering environmental sensor networks spatial regression test Data quality Data mining computer gap filling |
Zdroj: | Sensors, Vol 15, Iss 12, Pp 29765-29781 (2015) Sensors Volume 15 Issue 12 Pages 29765-29781 Sensors (Basel, Switzerland) |
ISSN: | 1424-8220 |
Popis: | This work proposes the design of Environmental Sensor Networks (ESN) through balancing robustness and redundancy. An Evolutionary Algorithm (EA) is employed to find the optimal placement of sensor nodes in the Region of Interest (RoI). Data quality issues are introduced to simulate their impact on the performance of the ESN. Spatial Regression Test (SRT) is also utilised to promote robustness in data quality of the designed ESN. The proposed method provides high network representativeness (fit for purpose) with minimum sensor redundancy (cost), and ensures robustness by enabling the network to continue to achieve its objectives when some sensors fail. |
Databáze: | OpenAIRE |
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