Know the IQ rating of your security system
Making the most of your investment in a new security system means knowing how smart your current system is. Specialist contributor Dr Rustom Kanga explains why.
Studies have shown that an operator watching two monitors misses 45 per cent of the action after 10 minutes and after 22 minutes he misses 95 per cent of the activity. This is in a relatively empty scene.
In a busy scene, it takes even less time for an operator to miss action on a screen. What are the chances that an operator watching hundreds and sometimes thousands of cameras would observe anything of use?
Organisations focused on security have realised the very large sums of money they have spent on cameras and control rooms provides them with little real security. The video recorders they have installed are useful after an event but have little value in preventing an incident.
Hence, there has now been the growing realisation for organisations that to get value from their security systems they need to add ‘intelligence’ such that the operator will be told when an incident happens or even better, BEFORE it happens. The system should be able to tell the operator that on Camera 235 a person has fallen down or that on Camera 650 a bag appears to have been abandoned.
Now that astute users of security are recognising that without intelligence their investments in security equipment are underutilised at best and at worst useless, there is a burgeoning industry of providers of such intelligence.
How can one tell the difference between hundreds and even thousands of suppliers which all purport to add intelligence to security systems?
At iOmniscient, we came up with an intelligence rating system for our own products which can of course be used more universally by users to define the intelligence of their own systems.
Detection and identification technologies
To start with, there are two major classes of intelligent technologies - those involving detection and those involving identification. Detection involves observing a scene and understanding what is happening in the scene. Identification involves knowing the identity of the person.
The measurement of human IQ is based on a normalized system. The average person in the population has an IQ rating of 100. That means 50 per cent of the population has a rating higher than 100 and the remainder has a rating below that.
A similar rating system was used on intelligent security products. Those algorithms involving enormous complexity mimicking the human brain were classified as requiring a high IQ while other techniques that were simple to implement were deemed to have a low IQ rating.
The products were rated as having an IQ from as low as 10 to as high as 180. As one would expect in looking at the market, there are many suppliers that offer the lower IQ capabilities. As the IQ rating increases, the number of players in the market decreases rapidly.
At the lowest level of the scale, the algorithms are based on video motion detection (VMD). VMD, in its simplest form, consists of comparing the pixels on one image with those on the next. If there is a difference, this means there was some change in the scene usually interpreted as motion. Such systems rated at around IQ 60 are widely available but of course as the IQ rating implies, they are of little value as they are prone to false alarms.
Not every pixel change is due to motion. Light variations, reflections on water, shadows and a host of other changes cause the change in pixels making such systems useful only to those who want to claim their systems have intelligence while not expecting them to do anything practical.
Next level of sophistication
At the next level of sophistication, systems can be set up to group the pixel changes between images as ‘blobs’ and to then track the movement of the blobs across the screen (IQ 100). The characteristics of the blobs (such as size or shape) can also be analysed and the system can therefore differentiate between people and small animals or between cars and trucks.
Even within an IQ level, there can be many variations in technology. It is quite simple to track a single person in a relatively empty scene. As the scene gets more crowded, the algorithm has to cope with blobs that merge and split. Tracking a particular person through a crowded scene can be a very complex task and not all companies who can supply a technology with this rating can necessarily cope with such scenes effectively.
Using this level of technology, it is also possible to detect objects left in a relatively empty scene as this just involves noting when a blob has split and where one part of the old blob remains stationary.
The next level of capability (IQ 110) involves being able to clearly define the ‘item’ that is being tracked, for example - people and to be able to count them accurately.
At this level of technology, one can detect loitering, running and slips and falls.
Not all behaviours are easy to detect
Behaviour can be culturally dependent and hence not all behaviours are easy to detect by a system. For instance, I observed a system designed to detect fighting. It worked well in the UK. However, it collapsed in Italy as it easily mistook two exuberant Italians meeting after a long separation as fighting.
As one gets to IQ 120, the technology moves from detecting and observing individuals to operating in crowded environments. Crowd management at this level can provide capabilities such as determining how many people are in a very crowded scene at a given time.
Finally one gets to IQ 140 which allows the detection of abandoned objects (or removed objects) in a crowded scene. This is useful in an environment such as an airport where luggage may be left unattended or in museums or warehouses where items may be stolen. Such systems have to cope with very long detection times (if the detection time is too low there would be thousands of nuisance alarms from passengers placing their bags down momentarily).
And with the long detection times, the system has to cope with significant obscuration (where the object is obscured for a significant period of time by passersby).
Finally at IQ 180, the system has the capability to do everything that can be done at IQ 140 but it does it even when the object may be invisible to the human eye because the object is tiny and with little contrast.
Often systems will do one or the other of these detections on a camera scene. A system that can do all of them at the same time has been defined as IQ Infinity.
Systems need to have certain core characteristics
All systems, no matter what their intelligence level, need to have certain core characteristics. Several of these features are architectural, though some do require a level of intelligence.
Architectural characteristics include:
* openness - the ability to take inputs from any camera, operate on any computer and interface with any video recording system
* scalability - the ability to grow from a single camera to thousands of cameras
* distribution - the ability to place the intelligence either centrally or remotely in a network.
Intelligence characteristics include:
* the ability to avoid nuisance alarms caused by extraneous factors such as light changes, water reflections or shadows, the ability to understand perspective and the ability to know if all the cameras can see properly and are operational. This is especially important if the system is prone to sabotage, vandalism or just bad weather.
Intelligence based on the view of a single camera
Most systems today provide intelligence based on the view of a single camera. For instance, the system can tell if a person enters a scene or leaves a bag based on a single camera view. The technology has now moved beyond that to using the intelligence gained from multiple cameras within a network to make higher level decisions. An example of this is for theme parks or airports where they may have long queues that extend beyond the view of a single camera.
By collecting information from multiple cameras, one can calculate the average waiting time for people in the queue.
Users need to ask - what is their system required to do?
Users need to ask themselves: "What is their system required to do?" Are you, as a user, happy to have a system that is only useful after the fact to review disasters or do you need to have one that can help you to pre-empt them? What types of events are important to you? Can your system help you to avoid these events or in the worst case, tell you instantly if one has occurred.
The IQ Rating system described in this feature will help you to assess the level of intelligence your system has and also it will allow you to determine what you need.