Crowdsourcing Situational Awareness (Crowd- SA) Navy SBIR FY2013.1 Sol No.: Navy SBIR FY2013.1 Topic No.: N131-063 Topic Title: Crowdsourcing Situational Awareness (Crowd- SA) Proposal No.: N131-063-0485 Firm: Modus Operandi, Inc. 709 South Harbor City Blvd., Suite 400 Melbourne, Florida 32901-1936 Contact: Teresa Nieten Phone: (321) 473-1426 Web Site: http://www.modusoperandi.com Abstract: The basic need in a crisis situation, whether it is a natural or unnatural disaster, political or social unrest, or some combination, is relevant, timely and accurate information, filtered to present the most pertinent data to the decision makers. Commanders have unique information requirements due to short timelines and unknown background data on their assigned Area of Operations. Crowdsourcing data, properly filtered and managed, provides an instant "quicklook" into the human terrain, atmospherics, and current events. This also assists the Intelligence Operational planners to direct their assets to confirm or deny conclusions drawn from the crowdsourcing data. Our solution, implemented as a monitoring system to world events, could act as a "first alert" capability that would indicate an upcoming problem or crisis well in advance of the typical news and intelligence channels. Modus Operandi proposes to develop a crowdsourcing system to analyze and fuse data from witnesses and participants to find relevant information in times of disaster or emerging crisis. The final system will accept input from the crowd, extract events and entities in the context of natural language, normalize the information, and fuse it with data from other sources using cloud-based distributed processing. Benefits: Our solution will improve the usage of crowdsourcing for emergency response and social/political unrest by combining the crowd with the cloud, in effect, it becomes a human sensor net, gathering information from people directly affected by and eyewitnesses to the developing crisis situation and processing it using cloud-based computing to efficiently process the incoming data, significantly reducing manual processing of pertinent intelligence. Our solution facilitates faster response time by tapping into embedded observers and when combined with sensor data such as aerial reconnaissance or weather stations, the information becomes multi-source intelligence data. The successful application of crowdsourcing data discovery, and distributed processing using a MapReduce framework will provide a useful tool for efficiently and effectively providing situational awareness for analysts and first response teams. From a macro perspective, the crowdsourcing data, combined with known gazetteer data, will provide the initial Human Terrain overlay used in the Intelligence Preparation of the response and provide a unique view of the Area of Operations (AO). This capability could be immediately applied to teams engaged with Humanitarian Aid (Police, Fire, and Medical personnel) and could have further applications in the areas of Retail Trend Analysis, Travel, Real Estate and Geo-demographic applications. Return