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Sensor Data Fusion and Event Detection

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Wireless Sensor Networks

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

Sensor data often contains noise, outliers, missing values, and a significant number of duplicate values. The causes of such data quality problems include the sensors’ internal errors, a harsh environment in which the sensors are deployed, and data loss occurring during wireless transmission. Sensor data fusion consists of three steps, data pre-processing, data mining, and data post-processing. This chapter discusses data pre-processing and data mining. Data pre-processing includes data cleaning, outlier detection, missing values recovery, data reduction, and data prediction, etc. Neighbourhood support and tempo-spatial pattern extraction are introduced and applied to a generic sensor state model for event detection. The concept of in-network database is also introduced by presenting WSNs as a virtual distributed database.

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Correspondence to Shuang-Hua Yang .

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Yang, SH. (2014). Sensor Data Fusion and Event Detection. In: Wireless Sensor Networks. Signals and Communication Technology. Springer, London. https://doi.org/10.1007/978-1-4471-5505-8_8

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  • DOI: https://doi.org/10.1007/978-1-4471-5505-8_8

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5504-1

  • Online ISBN: 978-1-4471-5505-8

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