eMontage: An Architecture for Rapid Integration of Situational Awareness Data at the Edge
May 2013 • Presentation
A presentation from the ninth annual SATURN conference, held in Minneapolis, MN, April 29 - May 3, 2013.
Software Engineering Institute
This presentation was created for a conference series or symposium and does not necessarily reflect the positions and views of the Software Engineering Institute.
First responders and others operating in crisis environments at the tactical edge increasingly make use of handheld devices in their missions. In such environments, rapid data integration for effective situational awareness is an important requirement. To address this use case, we designed a system called eMontage that allows rapid integration of data from remote situational-awareness data sources. This capability gives first responders and warfighters in resource-constrained environments access to relevant data on a single mobile device with a consistent user interface.
Specific objectives for eMontage include rapid incorporation of new data sources (e.g., sources unique to or available at the site, national and international sources, corporate sources, and charitable sources); minimized information load for users (i.e., only the right information at the right time); user control of that information load to the extent possible; and ease of use that reduces the user's training time and learning curve. An architecture for accessing and filtering data from multiple sources provides benefits such as combining data from real-time and historical sources, operating in connected or disconnected modes, supporting individual selection and filtering of data, and integrating data from multiple sources.
We will present the framework, architecture, alternatives, tradeoffs, and implementation details of the prototype. Key system characteristics of eMontage include rule-based runtime filtering, a unified user interface for all data sources, an extensible set of data sources, minimized bandwidth utilization, offloading of resource-intensive tasks, low latency, and disconnected operations. Our prototype solution enables users to construct geospatial data mashups that incorporate local and remote data from Department of Defense systems and other publicly available real-time and historical data sources such as Twitter, Foursquare, Flickr, and the National Weather Service.