6533b820fe1ef96bd127a451
RESEARCH PRODUCT
Context-awareness for multi-sensor data fusion in smart environments
Alessandra De PaolaPierluca FerraroGiuseppe Lo ReSalvatore Gagliosubject
Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniEngineeringMulti-sensor data fusionbusiness.industryProbabilistic logicContext awareneInferencecomputer.software_genreMachine learningSensor fusionTheoretical Computer ScienceActivity recognitionDynamic Bayesian NetworkHome automationComputer ScienceContext awarenessSmart environmentData miningArtificial intelligencebusinesscomputerDynamic Bayesian networkdescription
Multi-sensor data fusion is extensively used to merge data collected by heterogeneous sensors deployed in smart environments. However, data coming from sensors are often noisy and inaccurate, and thus probabilistic techniques, such as Dynamic Bayesian Networks, are often adopted to explicitly model the noise and uncertainty of data. This work proposes to improve the accuracy of probabilistic inference systems by including context information, and proves the suitability of such an approach in the application scenario of user activity recognition in a smart home environment. However, the selection of the most convenient set of context information to be considered is not a trivial task. To this end, we carried out an extensive experimental evaluation which shows that choosing the right combination of context information is fundamental to maximize the inference accuracy.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2016-01-01 |