Abstract
In recent years, advances in hardware technology have facilitated new ways of collecting data continuously. One such application is that of sensor data, which may continuously monitor large amounts of data for storage and processing. In this paper, we will discuss the general issues which arise in mining large amounts of sensor data. In many cases, the data patterns may evolve continuously, as a result of which it is necessary to design the mining algorithms effectively in order to account for changes in underlying structure of the data stream. This makes the solutions of the underlying problems even more difficult from an algorithmic and computational point of view. In this chapter we will provide an overview of the problem of data stream mining and the unique challenges that data stream mining poses to different kinds of sensor applications.
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© 2013 Springer Science+Business Media New York
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Aggarwal, C.C. (2013). Mining Sensor Data Streams. In: Aggarwal, C. (eds) Managing and Mining Sensor Data. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-6309-2_6
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DOI: https://doi.org/10.1007/978-1-4614-6309-2_6
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Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4614-6308-5
Online ISBN: 978-1-4614-6309-2
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