Video analytics refers to the automated ability to use the images captured by a video camera in a proactive manner. Examples would be monitoring the line at a cash register, where customers shop most frequently within your store, or if employees are or are not adhering to safety rules in a manufacturing facility. As the cost for this technology decreases, and the applications and benefits increase, we are seeing cameras in more and more places. They aren’t just for loss-prevention. The following information from videosurveilliance.com explains this tech trend.
What are Video Analytics?
Video analytics software was created to help review the growing hours of surveillance video that a security guard or system manager may never have time to watch – your video surveillance system is only as useful as the incidents you can capture and watch, and video analytics will help you find them.
Using video analytics makes your surveillance system more efficient, reduces the workload on security and management staff, and helps you capture the full value of security by making your IP camera system more intelligent in its work.
Video analytics software for security cameras is available in several forms; installed on your camera, on your NVR, or aTech s a 3rd party software you buy. Each version will do the same thing, however – monitor your videos to search for and alert you to activity.
Video analytics can be used for:
• Motion detection
• Facial recognition & license plate reading
• People counting & dwell time monitoring for retail stores
• Recognizing long lines at checkouts and sending alerts
Video analytics software comes with a wide range of features, making them easy to fit into any surveillance system. Choose from software that supports every system from the smallest system to large multi-campus systems. A variety of leading manufactures create video analytics software.
Video analytics for everyone
Video analytics or CCTV software has come a long way over the last few years in terms of capabilities and accessibility. In previous years, analytics were primarily needed and available to large, corporate or government systems, requiring powerful servers to run each application along with high-end infrastructure.
Now, due to maturing analytic engines and the exponential increase in camera and server processing power, analytics can be used by many different kinds of users and run a variety of environments. Analytics can run on the camera (edge) or on a server running multiple video streams or applications.
Choice on the edge
The growing prevalence of analytics on the edge offers systems flexibility and can significantly reduce the cost of the overall solution, as fewer servers are required to run the analytics. Edge base analytics can also lessen system bandwidth demands, as video can be transmitted from the camera only after being prioritized by the analytics.
With IP cameras, analytics present the same types of possibilities, adding in optional applications that build on the camera’s out of the box capabilities. Many premium cameras already possess the processing horsepower and available memory to do this today. It is simply a matter of time for an ecosystem of add-in functionality to become available.
In the analogue age, surveillance devices themselves were used purely as security solutions. Now that IP network, cameras have become so popular and especially because of the edge analytics they offer, the humble camera has become a business intelligence tool.
Analytics can offer such tools as heat mapping and queue monitoring for retail and hospitality, as well as people counting and foot traffic.
The processing power of camera and servers continues to grow exponentially whilst prices are steadily declining. As time passes and the camera’s processing power increases, its capability for hosting an ever-increasing array of analytic functions also increases.
Better decision making
Even with the great strides in improved effectiveness, increased accessibility and cost, the primary function of analytics is still to complement the role system operators, not to eliminate them.
Ultimately, analytics assist operators in making informed decisions by illuminating the unusual from the mundane. As the number of cameras being deployed and monitoring continues to increase. Better analytics can’t help but give the operator more reliable information, which in turn improves response time and effectiveness.
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