At this time, such clarifying language does not carry over into materials promoting the standard. For example, the Conclusion section of UL’s white paper states, “Video cameras tested and certified to UL 2802 ease the process of identifying video technology that meets the requirements of specific applications, enabling more effective comparisons of price and performance.”
While that sentence is not inaccurate, a non-expert reader won’t catch the critical significance of qualifying words like “ease” and “more.” Many marketers and writers will interpret the last phrase as “providing effective comparisons of price and performance” — making it seem like the test ratings are all that’s needed to make a camera selection.
In last year’s third quarter issue, the UL newsletter, “The Fire & Security Authority,” made the following statement: “The result of a UL 2802 test program is an objective set of performance scores for a camera’s image quality attributes.” Many readers will infer from those words that a camera that scores higher than another camera will provide a better image in all conditions; yet, the standard itself — which end-users will not see — refutes that inference.
Other statements like these and worse are being made already by companies who are enthusiastically embracing the standard, and as Frank Luntz states in his book Words that Work: “It’s not what you say, it’s what people hear.” That’s why there will be some problems.
What the Standard is Not
The standard is definitely not a substitute for the hard-won product experience of integrators, who understand the difference between the controlled environmental conditions of laboratory tests and real world deployment environments. It’s not a substitute for the knowledge and experience of security design consultants who invest significant time to obtain in-depth product performance knowledge.
The UL standard does not address these camera performance factors such as: CPU performance; multiple video stream support; video compression; strong operator authentication; basic network protocol support; secure (HTTPS) connections; SNMP and syslog protocols; video motion-detection analytics and other on-board analytics; auto-recovery from network error conditions; performance under various load conditions; camera diagnostic information; and mutually exclusive camera functionality.
Problems involving some of these factors can result in video images being stopped altogether, or can prevent the use of high-image-quality camera configurations. Mutually exclusive functionality is rarely identified in camera data sheets. For example, some cameras cannot support certain features if the camera’s low-light mode is activated. Just because a camera communicates over a network doesn’t mean that its network protocol support is complete — some network cameras crash if anyone performs a standard Nmap or Nessus network scan. Limited CPU processing capability can mean that if you configure multiple video streams with at high resolutions and frame rates, the camera may have trouble performing motion detection. An underperforming camera can mysteriously crash, resulting in no video at all — an obvious score of “0” for image quality.
Another problem relating to the standard is the unavoidable use of the term “image quality.” There is more than one meaning for the term, which is why it would be more appropriate to refer to UL 2802 as testing “technical image quality” — what the camera is capable of producing under laboratory test conditions.
Camera end-users, on the other hand, are interested in how well cameras perform in areas of interest for security, safety and business reasons. We could call that “functional image quality” — an entirely different subject. Lab conditions are optimized to support high image quality. From that perspective, most field conditions are compromised.
How will the camera perform given the job it has to do in the location where it will be installed? The final answer lies outside of the scope of UL 2802 testing. The actual situation is that guidance, rather than testing, is needed — plus expertise to take into account the many varying factors that affect video quality.