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Description:
CASA was a project aimed at developing a vision-based machine-learning software solution that automated identification of civil and military infrastructure details from overhead aerial and satellite imagery and pre-populates standardized survey questions in Esri Survey123 forms (used by US Army Civil Affairs) to document civil and military infrastructure. The software allows analysts to increase the accuracy and volume of collected data through optimized workflows with Esri Survey123 collection software and Esri ArcGIS Online, enabling superior institutional understanding of the operational environment.
Operational Impact:
CASA assists analysts by increasing both the volume of collected data and accuracy of infrastructure assessments through an efficient user interface that optimizes workflow. Superior documentation on existing civil and military infrastructure supports GPC Phase-0 activities, mission planning, and post-conflict transition in designated Areas of Operations.
Transition:
Production prototype software suite (TRL-8) was integrated into US Southern Command’s (SOUTHCOM) FOUO/CUI/IL4 Enhanced Domain Awareness (EDA) platform to support Humanitarian Assistance & Disaster Response (HADR) operations within the SOUTHCOM Area of Responsibility. CASA software is also deployed onto C5ISR’s DevOps environment “Road Runner” to support operational test and evaluation, and transitioned under the Civil Affairs Solution-Army Program of Record.