Big Data Analytics - Part 2

Blog Date:  5/15/2013
Author:  Ray Coulombe

Big Data is a name which has been given to masses of data that have been, or are continuously, assembled from an expanding variety of information sources. These sources may be internal or external to an organization; produce data that is structured, unstructured, or random; and which heretofore have defied conventional analysis. Now, companies such as IBM and RSA (division of EMC) are developing means to derive underlying value from these stores of data by surfacing trends, patterns, and apparent correlations.
Video presents special challenges. I heard cited at a recent conference a 2011 statistic stating that 220 million frames of video are recorded every second. Assuming an average recording rate of 10 fps, that’s 22 million cameras feeding storage media, which doesn’t seem unreasonable. As a sanity check, another 2011 study estimated nearly 2 million cameras in the UK alone, or about 1 for every 14 people. Given that IP CCTV cameras are now outselling analog cameras, and that network bandwidth and storage capacity are increasing while costs are decreasing, it’s safe to say that the amount of video stored per month will continue to increase, although it is not known how much of that will be archived beyond 30 days. This last point is significant. If it’s not kept for more than 30 days, there’s a finite time window for analysis. If big data analytics for video becomes a game changer, that in itself may argue for longer retention periods.
So what’s the opportunity? I believe the answer is in the correlation of captured images and sequences with similar material or with other data that is in or accessible by the system. We have an example of that (though not big data) in the retail market, where video is correlated with POS (point of sale) transactions. In this simple example, a transaction “tag” is placed on the video, allowing a ready view of what transpired at time of transaction. Other types of tags are time/date, alarm inputs, and those from video analytic engines. But when we scale up to big data to find events or to evolve relationships that are not obvious, there will be several requirements for the technology to work as intended.
Link to Complete Article as it appeared in Security Technology Executive Magazine


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