When security systems were purely analog, technicians would test the sharpness of each camera's image by laboriously connecting each, one at a time, to a specialized focusing monitor. With the transition to network video, installation technicians became more creative. Some used their PDAs or precariously balanced their laptops as they climbed ladders to test and retest the camera focus. Others used two-way radios to speak with someone watching a display at the central monitoring station who would give them live feedback as they adjusted each lens. Such an inefficient process inevitably required considerable time and manpower to execute, diverting a portion of a company's security budget that could otherwise have been invested in additional surveillance assets.
Today small optics motors are built into many network cameras that enable installers to use remote computers to manually or automatically fine-tune the focus as well as adjust the zoom angle to optimize the field of view. It's a more cost-efficient process that considerably reduces set-up time. This significant savings in labor costs ultimately lowers the overall total cost of ownership for a network surveillance system.
The motorized lens can also expedite remote maintenance checks and adjustments once the deployment goes live. Instead of setting up ladders and disrupting operations to readjust the field of view or the angle of the zoom, you can do it online via the computer. Installers can even program the camera to automatically self-adjust its focus on a regularly scheduled base, such as once a week.
Above: Built-in optics motor lets you adjust camera focus and zoom angle remotely.
Pixel counter: Instantly verify resolution
Another innovation in network camera technology is a pixel counter. In the past, installers lacked any tools that could accurately measure whether a camera was delivering the resolution a customer expected. Today, built-in pixel counting analytics let an installer look at a camera's field of view over the network and verify the exact pixel count being captured within various sections of the image frame. The calculations take a number of factors into account: sharpness of the overall image in the recording and viewing systems, the quality of the lens, and the lighting conditions of the scene under surveillance.
Above: A pixel counter verifies a camera's resolution remotely.
While standards have yet to be established in the United States, in some Europe countries law enforcement agencies are already specifying minimum pixel counts necessary to accurately identify people and objects for evidentiary purposes. For example, 20 pixels per foot has been deemed adequate for simple observation. For forensic review, however, the number should increase to 40 pixels per foot and for maximum clarity and recognition, resolution should be set around 80 pixels per foot.
Tampering alarms: Detect problems automatically
While a majority of innovations have been focused on the installation side of network surveillance video, attention is also being paid to the maintenance side. Some the newer network cameras incorporate remote focus motors as mentioned above. But many of today's network cameras also include sophisticated self-diagnostics and tampering alarms. If the camera detects that its lens has become dusty, its view deliberately obstructed or redirected, or that its operation is failing, it will send out an alarm to inform security of the problem so that immediate corrective measures can be taken. The incident at the Newark airport in January 2010, where reports indicated that the airline was unaware that one of its gate cameras was non-functioning, drives home the criticality of this feature. When you consider large retail operations where some chains have reported as many as 5 percent of their cameras essentially out-of-commission at any given time -- and oftentimes it's the very camera that would have had the perfect angle they needed -- the value of self-diagnosis and tampering alarms becomes even more self-evident.
Removing barriers to IP video deployment