A tour of BeAware – A situation awareness framework for control centers

Crowd^SA — towards adaptive and situation-driven crowd-sensing for disaster situation awareness

“…[21], [22] and CSI 3 (Collaborative Situation Awareness in Road Traffic Control). The conceptual architecture of the crowd-sensing level is based on insights and lessons learned from our currently on-going implementation of the devised crowd-sensing level, and initial case studies on real-world Twitter 4 data sets (cf.…”

“…1 Configuration CSI requires domain experts to specify templates describing the situations of interest, so-called Situation Evolution Types (SETs) [24], which are formulated in terms of a suitable Domain Ontology. Due to performance considerations, we decided to favor an object-relational implementation in CSI, as opposed to the semantic web technologies employed in our previous SAW framework BeAware [21] (namely RDF, the graph database Allegrograph, Lisp and Prolog), motivated by our comparative performance evaluation of the two approaches in [22]. Therefore, we use a UML-based approach for ontology engineering [25], employing the model-driven development tool Visual Paradigm 8 as OntologyDesigner.…”

Crowd-Sensing Meets Situation Awareness: A Research Roadmap for Crisis Management

“…When disaster strikes and crisis like earthquakes, grassfires or floods occur, human lives may depend upon emergency organizations' rapid establishment of an understanding of the situation at hand, termed Situation Awareness (SAW) [10], to take the appropriate decisions and actions in managing such crisis. Systems supporting human operators' SAW by fusing various sensor information have already proven their value in a range of different environmental monitoring applications (e.g., air and road traffic monitoring [3] or maritime surveillance [29]). The situational pictures observed in these domains employing automated situation assessment (SA) mainly base on information gained from traditional "hard" sensors [22].…”

“…The situational pictures observed in these domains employing automated situation assessment (SA) mainly base on information gained from traditional "hard" sensors [22]. Situations of interest are thereby either assessed on basis of predefined situation templates [3] or detecting anomalies within the environment [29]. Crisis Management.…”

“…2, before deriving a reference architecture and a set of evaluation criteria in Sec. 3. Based thereupon, we evaluate approaches for crowd-sensed SAW and elaborate on lessons learned in Sec.…”