title: On the relevance of using Bayesian belief networks in wireless sensor networks situation recognition.
abstract: Achieving situation recognition in ubiquitous sensor networks (USNs) is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA) technology. We propose a situation recognition framework where temporal probabilistic reasoning is used to derive and emerge situation awareness in ubiquitous sensor networks. Using data collected from an outdoor environment monitoring in the city of Cape Town, we illustrate the use of the ESA technology in terms of sensor system operating conditions and environmental situation recognition.
authors.affiliation: Department of Computer Science, University of Cape Town, 7707 Cape Town, South Africa. bagula@cs.uct.ac.za
authors.forename: Antoine B
authors.initials: AB
authors.lastname: Bagula
authors.forename: Isaac
authors.initials: I
authors.lastname: Osunmakinde
authors.forename: Marco
authors.initials: M
authors.lastname: Zennaro
mesh_terms: D001185:Artificial Intelligence; D001499:Bayes Theorem; D002947:Cities; D003195:Computer Communication Networks / Q000295:instrumentation / Q000706:statistics & numerical data; D004526:Efficiency; D004560:Electricity; D004784:Environmental Monitoring / Q000295:instrumentation / Q000379:methods; D006801:Humans; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods / Q000706:statistics & numerical data*; D058998:Remote Sensing Technology / Q000379:methods / Q000706:statistics & numerical data; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D013019:South Africa; D014584:User-Computer Interface; D059015:Wireless Technology / Q000706:statistics & numerical data