AIM - Gates Defense & Sickweather Phase 1 Demonstration скачать в хорошем качестве

AIM - Gates Defense & Sickweather Phase 1 Demonstration

Gates Defense: Automated Data Fusion and Predictive Analysis Problem Statement: Predictive analytics to identify potential hazardous material threats through automated data fusion and template development Overview: Gates Defense Systems is working with SOFWERX and Government partners to develop and demonstrate a proof of concept surveillance solution, which demonstrates an innovative dashboard leveraging COBRA’s unique COTS software platform – providing critical CBRNe mission data and analytics, alongside the leading edge situational awareness tool, Airbox Systems MOSAIC. The end state solution offering commanders a unique mission advantage, while placing front end users at the nexus of information. Technical Approach: Leverage and customize COBRA framework to aggregate, integrate, tag, share, and display disparate data sets/systems to enable users at all levels to access CBRN/CWMD capability-related information in order to support planning, training, and response to a broad range of potential CBRN/CWMD events. This technology will be multi-phased across design, model, test and deploy including: • Creating a vignette for the fixed site defense of an urban area designed to inform a military operation. • Creating a dashboard called CBRN IEW that utilizes JEM and JWARN, that is either cloud or locally hosted in conjunction with other existing applications. • Integrating the JEM and JWARN APIs into COBRA's open architecture. Sickweather - HAZMAT: Predictive Analytics to Identify Potential Hazardous Material Threats Problem Statement: Predictive analytics to identify potential hazardous material threats through automated data fusion and template development Overview: SICKWEATHER is working with SOFWERX and Government partners to develop and demonstrate a proof of concept surveillance solution utilizing their existing social listening technology and API architecture. Their forecasting model uses a combination of machine learning and seasonal models to forecast trends up to 15 weeks in advance at varying geographic levels, as well as imputing risk across geographic and political boundaries. Technical Approach: • Identify a contagion to use in the prototype demonstration. • Track the contagion in a chosen country. • Display regional hot spots of the contagion. • Provide predictions of the contagion spread. • Identify if military units contained in the region are experiencing localized events. • Provide forecast impacts to units.