Cloud-based Analytics of Satellite Imagery (CASI)

With the increasing availability of commercial satellite imagery, there is a need to develop a scalable, and robust architecture to support software analytics that can exploit and deliver time critical information to our warfighters. Commercial sensor data can augment existing national asset in providing more coverage, and advanced imaging capability that can be used to develop enhanced situational awareness. The proposed architecture must be able to support large-scale image processing and data analytics to enable monitoring, prediction, and assessment of a specific area of interest. Satellite imagery embeds both spatial and temporal information that must be managed and processed in such a manner that maintains its integrity and consistency. DZYNE Technologies propose to develop the Cloud-based Analytics of Satellite Imagery (CASI) system that leverages our experience in cloud database system for data management and our advanced Deep Learning algorithms for real-time image recognition, activity sequence learning and change detection to support these desired analytics. This proposed effort will develop an end-to-end solution that supports (a) a scalable cloud-based data store; (b) an extensible framework for software analytics; and (c) an automated imagery and video tagging using Deep Learning algorithms.