By Rod Coles, CEO & President, Bold Technologies
It’s now been over 20 years since the first IP Camera was released by Axis Communications back in 1996. Axis developed the system to monitor the sea for oil spills. It saved their customers from having to take two flights a day. Today, this method of video delivery is the norm; digital cameras are an everyday part of life, delivering daily cat videos to Facebook as well as monitoring our businesses and homes for security.
Video is a natural choice for security because as humans, we use our eyes more than any of our other senses. We see CCTV cameras everywhere, so why are the majority of alarm systems not video-enabled? If video is so natural, why is it not being used more in the alarm monitoring industry? Most cameras you see around a building are connected to a NVR/DVR within the building itself, or just recording without anyone watching.
Businesses that use IP video surveillance to protect their assets, such as car lots, can find it quite valuable, but it’s not realistic in most cases for someone to watch the feed 24/7. Video surveillance is often combined with other detection methods, such as a perimeter breach or motion detectors, which raise an alarm within automation software. The alarm is brought to an operator, and they decide what to do based on what they observe. The problem with this approach is that it can be error-prone; from detecting the breach, having the operator make a judgement call about what they see, how long they continue to watch, how far they go back and watch, etc.
The big disruptor to this problem is Video Analytics. Video Analytics are becoming commonplace for showing changes that may be happening within a picture to enhance and help an operator see movement. The current challenge with analytics is building context around the potential intrusion: is the movement a human or just a stray dog or cat? Is someone taking a short cut or are they loitering with intent? As analytics become more powerful, deciding whether to raise an alarm for a human to see or not can be made by the software. This removes error-prone human decision-making, and begins to make this kind of technology more usable in a traditional central station. Potentially, it could even replace traditional movement detectors.
One company that has gone further than any other with providing video in the traditional central station is I-View Now. I-View Now provides both live video and event based clips to show the operator what happened. The event based clips have pre-alarm which provides video from prior to a security event, the event itself, and immediately post-event. A typical clip is 15 seconds in length, which gives the operator a very focused view of what is happening, making it much easier for them to decide whether to progress the alarm or not. The I-View Now system uses traditional methods of security system signals, such as a PIR, and Video Analytics signals to generate alarms. I-View Now’s founder, Larry Folsom, said “Soon all video systems will have Video Analytics behind them. It’s the future of our industry.”
This move to Analytics is becoming possible because the processing power of equipment like cameras and servers is growing exponentially. This allows more processing power on the “Edge.” Edge computing is a method of optimizing cloud computing systems by performing data processing at the edge of the network, near the source of the data. Conversely, the advent of cloud computing is allowing complex analytics to take place in the cloud, effectively bringing huge power to even the dumbest device in the field.
False alarms continue to be the biggest issue facing the alarm monitoring industry right now. They are primarily caused by motion detectors (PIRS), but also human error, low batteries, unsecured doors and windows, pets, rodents, insects, and even poor installations. But if video analytics can distinguish a human from a pet, it can distinguish a child’s balloon floating around, and other non-threatening types of movement. Low batteries don’t affect its performance the same way they affect motion detectors. So, shouldn’t this be the natural way forward for the security industry?
The biggest objection is privacy. How do you feel about cameras watching your every move? How do you feel about those images being streamed into the cloud? It’s unnerving in a domestic environment. In a commercial environment, there are other privacy issues, such as commercial secrecy.
Maybe it’s time for a new type of detector…let’s call it an “Optical Analytical Sensor.” Now, as far as I am aware, this device doesn’t yet exist. But it could work on the “Edge” and receive new, updated analytics as they change, but not be able to transmit video. It would have no video storage; all it could do is pass events to a monitoring system. These events would include a description, such as “Human, identified as ‘Rod Coles,’ 98% confidence level,” but no video. The nice thing about this approach is the bandwidth requirements, often still an issue with video, would not exist.
Now, let’s take it further. We could calibrate these devices to recognize family members and friends. User awareness is a critical part of taking smart home systems to the next level. By recognizing who is in a home or business, the system can begin to make smart decisions. For example, why would we need to enter a code to disarm an alarm system if the Optical Analytical Sensor recognized that it was a valid user of the system and automatically did it for us?
What about a commercial application? If you needed a fully secure environment, you could have a permanently armed system. The Optical Analytical Sensor would just ignore the individuals who are allowed and generate an alarm for anyone who wasn’t. You could easily create areas that were off limits to certain people. You could link the system to access or door control and integrate one more technology into the mix. A more traditional approach could be implemented which armed the system “AWAY” if it didn’t detect anyone moving around for a set period, or even better, the system could track when users leave and then arm.
It’s easy to see how video surveillance with Video Analytics could improve security applications, but related industries such as PERS and Health and Safety could also have huge changes as analytics become more powerful. Additionally, retail organizations can benefit from being able to monitor the flow of people in and out of their stores, where they go, what their demographics are, etc.
Ultimately, good analytics will enable IP video surveillance to become more widespread within the Alarm Monitoring space. It’s only going to get better as more intelligence is built into these systems.