Probabilistic Processing of Interval-valued Sensor Data


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Evers, Sander and Fokkinga, Maarten M. and Apers, Peter M.G. (2008) Probabilistic Processing of Interval-valued Sensor Data. In: 5th International Workshop on Data Management for Sensor Networks, DMSN, 24 Aug 2008, Auckland, New Zealand (pp. pp. 42-48).

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Abstract:When dealing with sensors with different time resolutions, it is desirable to model a sensor reading as pertaining to a time interval rather than a unit of time. We introduce two variants on the Hidden Markov Model in which this is possible: a reading extends over an arbitrary number of hidden states. We derive inference algorithms for the models, and analyse their efficiency. For this, we introduce a new method: we start with an inefficient algorithm directly derived from the model, and visually optimize it using a sum-factor diagram.
Item Type:Conference or Workshop Item
Copyright:© 2008 ACM
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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Link to this item:http://purl.utwente.nl/publications/64883
Official URL:http://doi.acm.org/10.1145/1402050.1402060
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Metis ID: 251087