SBIR-STTR Award

Boston Fusion Corp. and Arizona State University will research and develop REsilience & Stability in DENse Terrains (RESIDENT), a multi-model, multi-scale framework for assessing indicators of stability and resilience in dense urban environments. Our team consists of subject matter experts in the Social and Computer Sciences providing the bedrock on which to build accurate mathematical models of urban stability at multiple socio-cultural and geo-spatial scales. We will advance the state-of-the-art in stability situational awareness and predictive capabilities by simultaneously encapsulating multiple computational social models within a single framework. During Phase I, we will develop an adaptive ontology of stability indicators using a multi-layer graph representation. We will develop innovative methods for near real-time data ingestion, entity and event extraction, model selection and execution, and socio-behavioral factor synthesis. In Phase II, we will refine and harden our algorithms, extend our framework to include additional stability and resilience models, extend the analysis to simultaneously encompass multiple geo-spatial and temporal scales, and work with transition partners throughout the Phase II effort to ensure transition success.

Boston Fusion Corp. and Arizona State University will research and develop REsilience & Stability in DENse Terrains (RESIDENT), a multi-modal, multi-model, multi-scale framework for assessing indicators of stability and resilience in dense urban environments. Our team consists of subject matter experts in the Social and Computer Sciences providing the bedrock on which to build accurate mathematical models of urban stability at multiple socio-cultural, geo-spatial, and temporal scales. We will advance the state-of-the-art in stability situational awareness and predictive capabilities by simultaneously encapsulating multiple computational social models within a single framework. During Phase I, we developed a structured ontology of stability indicators, implemented a quantitative social science model in software, and proved the concept with real-world open-source data for two use-case locations. In Phase II, we will extend the ontology to include additional universal social science theories as resilience indicators, implement them in software and use real-world data to quantify resilience for multiple dense urban environments. In addition, we will develop a novel, supplementary approach to measuring resilience based on wastewater biomarkers. We will refine and harden our algorithms and work with transition partners throughout the Phase II effort to ensure transition success.