PROBLEMS WITH VIDEO ANALYTICS CCTV SYSTEM

 Top 3 Problems with Video Analytics CCTV system:

• Eliminating false alerts

• System maintenance too difficult

• Cost of System too high

Eliminating false alerts

Since the goal of video analytics is to reduce or eliminate human involvement, eliminating false alerts is necessary to accomplish this. Each alert not only requires a human assessment but if found to be false, it increases emotional and organizational frustration with the system. Most system integrators are familiar with false alarms from burglar alarm systems and the frustration these cause.

On average, burglar alarm system false alarms per house. Many people do not experience false alarms of their burglar system for months. In contrast, many video analytic systems can generate dozens of false alarms per day. This creates a far greater issue than anything one is accustomed to with burglar alarms. Plus, with such alarms happening many times throughout the day, it can become an operational burden. Not all video analytics systems generate lots of false alarms but many do. These issues have been the major limitation of the integrators and end-users trying video analytics.

System maintenance too difficult

System maintenance is often overlooked and a somewhat hidden issue in video analytics. Over a period of weeks or months, a video analytic system’s false alerts can start rising considerably due to changes in the environment, weather and the position of the sun. This can suddenly and surprisingly cause major problems with the system. Not only is the increase in false alerts a problem, the perceived risk that the system could unexpectedly fail in the future creates a significant problem in trust. If your perimeter surveillance stops functioning properly one day, you have a serious flaw in your overall security implementation. This has been a cause of a number of video analytic system failures. The systems, already purchased, simply get put aside, becoming a very expensive testament to not buying or referring one’s colleagues to video analytics. Not all video analytic systems exhibit such behaviour but you would be prudent to carefully check references to verify that existing systems have been operating for a long period of time without any major degradation.

Cost of system too high

While you can find inexpensive video analytic systems today, these system tend to exhibit problems 1 and 2, high false alerts and poor system maintenance. Indeed video analytic systems that only cost $100-$200 generally have significant operational problems. One common feature of systems that work is that the complete price for hardware and software is usually $500 or more per channel for the analytics. Just because a video analytic system is expensive obviously does not mean it is good. However, significant investments are required to develop a system that is robust and works well in the real world. The developer needs to make the video analytic system “intelligent” enough to handle differences in lighting, depth, position of the sun, weather, etc. Doing this involves building more complex or sophisticated programs. Such programs almost always require significantly more computing hardware to execute and substantially higher capital investment in writing, testing and optimizing the program. All of these impact the price of the product.

The challenge is that it is basically impossible to see this from marketing demonstrations because, from a demo, all systems invariably tend to look alike. This of course has the vicious effect of encouraging people to choose cheaper systems that are more likely to generate high false alerts and be unmaintainable. If you select a system that works, the cost per camera can make it difficult to justify the expense. Nevertheless, for video analytics to grow in the private sector, they will not only need to work, they will be required to generate.