The MauveDB Project

The MauveDB project is motivated by the tremendous increase in the number of distributed measurement infrastructures such as wireless sensor networks that continuously generate invaluable data about our everyday world. However, the potential of this data has been hard to realize mainly because of the typically incomplete, imprecise, erroneous, and uncertain nature of the data generated. The MauveDB project aims to develop abstractions that make it easy for users and application developers to continuously apply statistical modeling tools to streaming sensor data. Such statistical models can be used for data cleaning, prediction, interpolation, anomaly detection and for inferring hidden variables from the data, thus addressing many of the challenges in managing sensor data.

MauveDB supports a new abstraction called "model-based views" to achieve the above goal. A model-based view is analogous to a traditional database view in that it can be used to present a consistent "view" of the underlying data to the user. However, as opposed to a traditional database view, a model-based view is defined using a statistical model instead of an SQL query. This not only significantly enriches the user interaction with the sensed data, but also results in more efficient processing of data.

A brief overview of the MauveDB project and the underlying technology


Project Participants

External Collaborators


This material is based upon work supported in part by the National Science Foundation under Grants 0546136, and 0509220. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.