Definition
The data generated by sensor networks or other distributed measurement infrastructures is typically incomplete, imprecise, and often erroneous, such that it is not an accurate representation of physical reality. To map raw sensor readings onto physical reality, a mathematical description, a model, of the underlying system or process is required to complement the sensor data. Models can help provide more robust interpretations of sensor readings: by accounting for spatial or temporal biases in the observed data, by identifying sensors that are providing faulty data, by extrapolating the values of missing sensor data, or by inferring hidden variables that may not be directly observable. Models also offer a principled approach to predict future states of a system. Finally, since models incorporate spatio-temporal correlations in the environment (which tend to be very strong in many monitoring applications), they lead...
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Deshpande, A., Guestrin, C., Madden, S. (2009). Model-based Querying in Sensor Networks. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_222
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DOI: https://doi.org/10.1007/978-0-387-39940-9_222
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