This paper describes our work in progress on an approach and technology for providing integrated data access in situational awareness applications – particularly for disaster and emergency response. The key new aspect of our work is an approach where information aggregation, processing, and integration capabilities are offered as a service to any new application builder. Further, we provide a f...

Situational awareness applications used in disaster response and tactical scenarios require efficient communication without support from a fixed infrastructure. As commercial off-the-shelf mobile phones and tablets become cheaper, they are increasingly deployed in volatile ad-hoc environments. Despite wide use, networking in an efficient and distributed way remains as an active research area, a...

Automatic language processing systems depend on, among others factors, the effectiveness in modeling human cognitive abilities, including the capacity to draw inferences about prototypical or expected sequences of events and their temporal order. Appropriate response to a crisis is as important for public security as are efforts to prevent any such natural or man made disaster. Recent research ...

This paper presents a multi-perspective vision-based analysis of people and vehicle activities for the enhancement of situational awareness. Multiple perspectives provide a useful invariant feature of object in image, i.e., the footage area on the ground. Moving objects are detected in image domain, and tracking results of the objects are represented in projection domain using planar homography...

Sentiment analysis refers to the class of computational and natural language processing based techniques used to identify, extract or characterize subjective information, such as opinions, expressed in a given piece of text. The main purpose of sentiment analysis is to classify a writer’s attitude towards various topics into positive, negative or neutral categories. Sentiment analysis has many ...