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Video Analytics is a hot technology, but can your investment provide a financial payback?


Visentry's solution uses video analytics from VideoIQ to identify people and cars that cross configured perimeter boundaries. Analog cameras feed an on-site VideoIQ server. Standard DSL lines transport video and real-time alerts from the dealer site to Visentry's central monitoring station where monitoring personal are attentive to the alarms and the associated video. When Visentry personnel are alerted to suspicious behavior, they warn the suspect with an audio announcement that is delivered over the DSL connection. Local police are notified if the warnings are ignored.

Nearby Paragon Honda in Queens , N.Y. , eliminated two of its security guards for a monthly savings of $9,000. Paragon pays $800-$1,000 per month for the surveillance service at each site. The installed cost of the overall system, including cameras, analytics and video recorder was about $45,000 per site. In addition to the security benefit, the Paragon ownership uses Web-based access to the system on a daily basis to remotely view activity at each of its four locations.

According to Yona Wieder, Visentry CEO, the company could not practically provide its service without the use of video analytics to identify perimeter violations. The analytics allow Visentry's monitoring personnel to effectively view a large number of cameras across multiple sites.

Prior to installing a VideoIQ system, one of Wieder's customers used a fence sensor and another used photoelectric motion detectors. In each case, the previous alarm monitoring company “quit” because they could not deal with the false alarms. “ When we installed our system at the dealership we tried to use part of the fence (sensor) in conjunction with our cameras,” Wieder explains, “but we stopped using the fence sensors because wind was causing too many alarms .”

Adds Doug Marman, CTO of VideoIQ: “[The system] knows how to separate out changes in the background. It learns the scene and knows to ignore water fountains, moving escalators, and all forms of weather, such as rain, snow and lightning. [The system] recognizes all of those as changes in the background, so that it can focus on detecting people, vehicles or boats.”

Analytics for “Tail Gate” Detection

San Francisco International Airport (SFO) has deployed Vidient's SmartCatch system to replace more than 15 security guards. Like all U.S. airports, SFO prevents unauthorized access to secure areas containing baggage and aircraft. A common problem around these areas is the practice of “tail-gating” or “piggy-backing” -- when an authorized person gains access to an area with a badge and is then followed by a second person who does not swipe a card before the door closes. The situation usually involves lazy employees who are not following the established access control procedures. This practice is not only an obvious security threat, but the TSA imposes hefty fines on the airports for violations.

The Vidient analytics alert a central monitoring station when two or more people enter a secure area with a single access authentication. The analytics identify the number of people passing through the area, and the access control system indicates how many authentications occur. When violations occur, the central station is provided with video pop-ups and audible alarms.

The airport has eliminated more than 15 contracted security guards from these secure doors, according to Michael McCarron, director of community affairs for SFO. The staff reduction results in an annual savings of more than $1.2 million.

McCarron emphasized that the analytics are one component of the airport's evolving security system. The Vidient system has improved over time, as the analytics are being perfected -- resulting in fewer false alarms.

Analytics for Parking Lot Fraud

The City of Tampa 's Parking Division has increased revenues by more than 143 percent in a three-year period using the AutoVu system from Genetec.

Previously, parking division officers identified delinquent parking ticket holders and bootable vehicles through manual inspection of license plates covering more than 16,000 city parking spaces in garages, lots and on-street parking. With the installation of the system, a parking division vehicle is equipped with cameras and mobile PC running the AutoVu Mobile License Plate Recognition Software (LPR) software. As the vehicle is driven through parking facilities and streets, the system detects and reads the license plates of vehicles that are parked in parallel, at 45- and 90-degree angles. Once the plates are identified, the system checks for a match within an onboard database of delinquent motorists that is updated by the Tampa Parking Division's central server. When a match is detected, the system generates an alarm notifying the officer that a bootable vehicle has been detected.