Abstract
Requirement of air quality has become higher with the living standard development and population increase. Therefore, establish the efficient ambient air data detection and fusion service system based on wireless sensor network and device cloud will be more convenient for searching existent problems that can figure them out with benefit living and leave away from the damage of air pollution. Moreover, in order to improve the accuracy and reliability of multi-source heterogeneous data in collection process according to the analysis of the limitations and the features of data collected, a proper data fusion approach based on extended Dempster-Shafer theory is proposed to expose the faulty information of sensor nodes for monitoring service. Results validate that the service can effectively improve the ability in terms of flexibility and extensibility, decrease the inherent uncertainty of the signal detection and reduce the decision-making risk.
Published Version
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