Analytics improve IP surveillance: IP-based hardware edge devices, such as IP cameras and encoders, can sidestep performance issues.

Enterprise networks today are increasingly tying their security solutions together with their network infrastructure to take advantage of the benefits a network-based solution has to offer. That includes the ability to integrate security with day-to-day functions, such as risk management, human resources, asset management and IT operations.

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Specific to physical security and surveillance systems, a network-based solution affords access to real-time video from anywhere and the ability to archive images and data in a central location--and monitor devices to identify potential problems, such as power failure to a camera.

Despite these advancements, networking professionals still worry about the impact of an IP surveillance system, paired with other capabilities, on the network. These concerns only increase as security professionals look to connect more devices and solutions on the network, including video analytics appliances.

Video analytics, or intelligent video management, has brought improvements in automating security surveillance. Instead of reacting to an incident minutes or, in some cases, hours, after someone breaches a secure area, video analytics enables security guards to receive an immediate pre-warning alert to an event with technology that can visually detect an intruder and then track that individual as he enters a facility.

IP-based surveillance systems and video analytics can successfully reside on an existing enterprise network with limited liabilities. Not only do these two solutions provide a surveillance solution to reduce theft, monitor perimeters and deliver proactive alerts to incidents, some systems on the market today require minimal bandwidth on the front end by operating on the edge of the network.

Today's enterprise networks often provide access across multiple buildings and, in many instances, across several states or countries. With this increasing demand for connectivity, however, comes risk. How much bandwidth does the network have? How secure is the network and what kind of functions will slow it down?

In recent years, video surveillance systems have been removed from the siloed environments of yesterday--with their own cabling, network servers and separate dedicated management-to IP-based systems that reside on a single unified network, with shared infrastructure and connectivity to the entire IT backbone, based on standard consolidated management frameworks.

For some IT professionals, adding surveillance systems and other security capabilities onto the network can be a challenging proposition. Video often contains large streams of data, especially when security professionals demand quality video. Today, those in the security industry expect high-resolution, full-motion video and audio. Slow frame rates are no longer acceptable for applications that require video to clearly show a person's face or other details in the footage, such as the dollar amount on a cash register.

With video surveillance a 24/7 business, what assurances are there that the network is not going to be overloaded by video ? A significant amount of video recorded today does not contain any relevant or actionable data--a surveillance camera can literally record video for hours before a person of interest walks into the field of view, or a suspicious car drives into a monitored parking lot late at night.

To limit the strain on the network, there are a few methods IT professionals can deploy, such as recording video at the edge, using compression technology and tweaking the resolution and bit rate of the video stream itself. When security professionals seek incremental value from surveillance, however, they might consider video analytics.

Traditionally, video analytics has required an onsite IT expert for implementation, because a number of the systems on the market today are software-based, and require a dedicated PC to operate, as well as hours of setup time.

Such network-based surveillance and centralized video analytics solutions can choke the system, however, if not set up properly. They require that information be constantly transmitted to a central location or server for processing and storage. Then, to view that data or video, additional bandwidth is needed to retrieve the information. These solutions can require a large amount of bandwidth, both to view the content and store hundreds of hours of video for back processing.

The market is seeing the migration toward IP-based hardware edge devices with built-in video analytics, such as IP cameras and encoders. Deploying an edge device is one method to reduce the strain on the network in terms of system requirements and bandwidth. When smart cameras and encoders process images at the edge, they record or transmit only important events-for example, only when someone enters a predefined area that is under surveillance, such as a perimeter along a fence. Other video methods transmit or record all video processed, including stagnant video when no one has entered the field of view.

This distributed approach for video analytics makes surveillance easier for network administrators to adopt. It limits the risks associated with overloading the system by enabling administrators to predetermine what video is important to view and keep, and which video is not pertinent.

For some companies, a full software-based approach to video analytics might be the best way to go. Still, others will find that edge-based video analytics devices provide the full-fledged capabilities required, without potentially choking the system or calling for a complete system redesign.

Dvir Doron is vice president of marketing for ioimage. Denton. Texas.

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