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Title: A survey on data quality for dependable monitoring in wireless sensor networks
Authors: Jesus, G.
Casimiro, A.
Oliveira, A.
Keywords: Wireless sensor networks;Dependability;Machine learning;Monitoring;Data quality;Sensor fusion
Issue Date: 2-Sep-2017
Publisher: MDPI
Abstract: Wireless sensor networks are being increasingly used in several application areas, particularly to collect data and monitor physical processes. Non-functional requirements, like reliability, security or availability, are often important and must be accounted for in the application development. For that purpose, there is a large body of knowledge on dependability techniques for distributed systems, which provide a good basis to understand how to satisfy these non-functional requirements of WSN-based monitoring applications. Given the data-centric nature of monitoring applications, it is of particular importance to ensure that data are reliable or, more generically, that they have the necessary quality. In this survey, we look into the problem of ensuring the desired quality of data for dependable monitoring using WSNs. We take a dependability-oriented perspective, reviewing the possible impairments to dependability and the prominent existing solutions to solve or mitigate these impairments. Despite the variety of components that may form a WSN-based monitoring system, we give particular attention to understanding which faults can affect sensors, how they can affect the quality of the information and how this quality can be improved and quantified.
Appears in Collections:DHA/GTI - Comunicações a congressos e artigos de revista

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