From driverless cars to commercial and home security systems to law enforcement surveillance, body cameras and digital evidence, digital video capture is now rising at an exponential rate. Much of this capture is retained for a period of time from a few hours to a couple of weeks, to preserve as important documentation in case of an event later discovered, such as a burglary or accident.

The amount of data captured and stored is expanding in several dimensions at once:

  1. The number of cameras is rapidly growing.
  2. Video resolution is improving.
  3. The desired retention period gets ever longer.

Distributed object storage is the only technology capable of handling the amounts of data generated. The pending technology wave for video is the various kinds of analysis that can be done on it after it is captured. Video from driverless cars will be used to identify road problems, debris, and obstructions. In Caringo’s hometown of Austin, Google driverless cars are a hot topic. According to an article in Silicon Hills News, Google began testing its self-driving prototype vehicles on Austin streets in September of 2015.

Coincidentally, Caringo’s User Interface Team Creative Lead, Catherine Malloy (aka, Cathy), and her daughter were among the six artists who had their designs selected to be painted on driverless cars (Cathy’s design is pictured above). As part of the prize, the artists had the opportunity to ride in the driverless cars. Cathy told me that “Riding in Google’s self-driving car and watching on the engineer’s laptop display how the car ‘sees’ its surroundings in real time was amazing. The amount of data required to ensure its safe operation is enormous. From traffic lights and construction barrels to pedestrians and even squirrels, the vehicles use high-resolution maps that are far more detailed than the standard Google maps.”

The practical use cases for video data storage hold tremendous possibility. Eventually, store video will be used to generate customer demographics and visit frequency. At some point, you will be able to ask your home video system where you put the cork wreath from last Christmas that you now cannot find. This kind of post-analysis will require the ability to annotate video captured as objects with useful metadata about what is on the video, as determined by various kinds of image analyzers. Future object storage will need not only to scale in storage and number of objects, but also to support that kind of annotation.

These possibilities fuel our innovation at Caringo. In our decade of providing software-defined object storage, we’ve seen explosive growth in data, and we know that trend will only continue.