Digital Tracking Cloud Distributed Architecture for Detection of Faint NEAs

There is an exponential volume of captured images, millions of captures taken every night being processed and scrutinized. Big Data analysis has become essential for the study of the solar system, discovery and orbital knowledge of the asteroids. This analysis often requires more advanced algorithms capable of processing the available data and solve the essential problems in almost real time. One such problem that needs very rapid investigation involves the detection of Near Earth Asteroids(NEAs) and their orbit refinement which should answer the question "will the Earth collide in the future with any hazardous asteroid?". This paper proposes a cloud distributed architecture meant to render near real-time results, focusing on the image stacking techniques aimed to detect very faint moving objects, and pairing of unknown objects with known orbits for asteroid discovery and identification.