Specialized iOmniscient Video Analytics Capabilities for a Smart City - As an example, in cities one often has to manage queues. iOmniscient offers a queue management product that uses a combination of the capabilities of the counting products, the crowd management product and the Face Recognition product to provide a capability which provides the user with information such as the average waiting time in the queue, the proportion of people who leave the queue before they get to the end of it and so on.  

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Driver Match The Face Recognition and License Plate Recognition system can be used together. In public car parks vehicles may sometimes be driven out by someone other than the driver who brought the vehicle in. Very often this is a symptom of a vehicle theft. Experience shows that it is often insufficient to use humans at checkpoints to detect such thefts of vehicles. The Driver Match system recognizes the number plate of the vehicle being driven as well as the face of the driver and checks that the driver is the one who is authorized to drive that vehicle.  

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Multi-lingual License Plate Recognition iOmniscient’s License Plate Recognition system can recognize plates from over 100 countries. It does not require any external trigger (e.g. motion induction loops) to recognize that a vehicle is in view and needs to be recognized. It is all done with video. Operating at high accuracy even at high speeds, such an integrated License Plate Recognition system is critical in any Smart City implementation.  

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Recognition Technologies by iOmniscient: All the technologies described so far are detection technologies. They analyze a wide scene and detect behaviors of humans or vehicles in the scene. There is a parallel Video Analytic technology for the recognition of humans and vehicles.  

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iOmniscient has developed a unique Jump to Event capability associated with an iQ-140 level system that goes way beyond this. It enables the user to jump back to a pre-defined time before the event started. Hence in our example of the abandoned bag, at the press of a button the user can jump back in time not just before the bag was detected but before it was first brought into the scene and abandoned. The user can immediately review both the event and the preceding period of video footage and gain important information on who brought the bag in and the person’s current location if he is still  

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Immediate Response with “Jump to Event” The old method of using Pre and Post Alarm video to determine what happened during an incident has become obsolete because in today’s world the incidents themselves are becoming much more complex. The required information can now be available in real-time from iOmniscient. The “Jump to Event” capability takes information retrieval to a new level of sophistication. In simpler system, a few seconds of video may be retrieved showing the moments just before and just after the event. This works when the event is something that happens at a fixed point in time  

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Simple object detection with iQ-100 which is available from many suppliers (Left). Sophisticated object detection in a crowd which is only available from iOmniscient iQ-140, (Right).  

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A smarter system would be able to count people and vehicles accurately. In fact the same system should be able to classify objects (e.g. trucks, cars and bikes) and count each category individually. An even more sophisticated system is capable of more complex behavior analysis such as the ability to detect slips and falls. This would be considered to be quite a smart system. People can fall down for many reasons. They could have been assaulted; they may have had an accident; they may just slip and fall. The system will detect such an event and enable resources to be deployed to help the person  

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As with humans, not all systems are equally smart. To understand how smart your system is, we have put together an iQ Rating Chart. iOmniscient’s behaviour analytics products are categorised as per their level of intelligence – their iQ Rating. Just for reference, the average iQ of the human population is 100. Half the population has an iQ of more than 100 while the other half has less. A surveillance system with a rating below 90 would be classified as a system with very basic or limited intelligence. Between 90 and 110 the system has average intelligence. At an iQ of 120 the system can be co  

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ONLY BY iOmniscient - The increasing accuracy of facial recognition systems and the number of applications for this technology have raised the issue of privacy of people whose face images are being captured and analyzed.  

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