Big data is an enormous amount of data which is huge in size. In short such data is so large and complex that none of the traditional data management tools is able to store or process it efficiently. To quote a few examples, the New York Stock Exchange generates 1024 gigabytes which are equivalent to 1 terabyte of new trade data per day. 500 terabytes of new data get inserted into Facebook every day. A jet engine can generate about 10 terabytes in 30 minutes.
Big Data could be structured in the form of fixed format, unstructured and semi-structured. This was relatively less relevant when volumes were small. Currently, data has reached the level of billion terabytes.
Data is the beginning of a military operation. Militaries, in the current environment, use big data for surveillance, processing of intelligence, prioritizing of targets, engagement, post-strike damage assessment. The entire fields of military logistics and human resource management call for data management.
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It would be interesting to analyse all these aspects comprehensively. In the field of surveillance, it would be essential to know the areas to focus and the likelihood of attaining the best results with devices. Today, surveillance includes a plethora of devices. These are satellites, unmanned aerial vehicles, aerostats, Airborne Warning and Control System (AWACS), reconnaissance helicopters and aircraft, ground-based electronic devices and human intelligence.
The data collected is enormous. To give an example, the United States ARGUS ground surveillance system mounted on a UAV collects more than 40 gigabytes of information per second. ARGUS-IS is a Composite Focal Plane Array (CFPA) assembly of 368 overlapping FPAs, imaging a wide persistent area at 10 Hz. The device, if the need arises, could also be mounted on a manned platform.
Each FPA provides high-resolution imagery which is combined with neighbouring FPAs to perform the functions of creating video windows, detect and track moving vehicle, reach back into the forensic archive and generate 3D models.