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iOmniscient specializes in use cases that excel in complex, extremely crowded and realistic environments – doing things that no one else can do having 40+ International Patented VA solutions. These can easily be customized for a specific environment by combining the appropriate Analytics from iOmniscient’s comprehensive portfolio of over 100 capabilities.  

2019-07-15  Read More

The unique technology foundation has enabled iOmniscient to remain a technology leader in the global market and to survive challenging periods including the global financial crisis. This has been possible because of the unique capabilities and robustness of the technology that remains ahead of it's time.  

2019-07-15  Read More

iOmniscient’s brand is recognized worldwide winning numerous international awards on EVERY continent including the “Best CCTV System of the Year” for its Face Recognition in a Crowd and the Global Security Challenge for Crowded Scenes.  

2019-07-15  Read More


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As a pioneer in Video Analytics with almost 2 decades of commercial experience (since 2001) iOmniscient is the longest standing independent Analytics company in the world.  

2019-07-15  Read More

iOmniscient proudly and confidently ask any other Video Analytic player to fill out the last column and also ask them to test out iOmniscient's footage like the moving crowd footage. Non will be able to match up to iOmniscient.  

2019-07-15  Read More

iOmniscient can also use behavior to trigger face recognition like if a suspect is loitering too many times at the ATM area then we can enroll this suspect automatically and alert the next bank location to watch out this person.  

2019-07-15  Read More

Based on 2-megapixel camera, iOmniscient needs only ONE camera to see 20-meter and able to cover ONE big corridor (4m wide at the narrowest point to 8m wide at the furthest point) whereas NEC if using the same 2-megapixel camera will need 6 cameras to cover the same corridor but can see only 3 meters of distance  

2019-07-15  Read More

Our robust 3D and low resolution capabilities can allow us to see very far with wider face angle so we build many different use cases such as tracking suspects across non-overlapping cameras. iOmniscient is not like NEC needs to ask the suspect to stand still to cooperate and take a nice frontal picture then NEC system may work. iOmniscient can track even in uncontrolled crowds using hand held camera, body camera or PTZ cameras see the video  

2019-07-15  Read More

NEC’s system is built for co-operative individuals using 2D image. iOmniscient has built our system using 3D using lower resolution so we can see far catching 75 faces using just 1 megapixel camera whereas NEC needs 4K cameras to catch few faces. Our 3D low resolution capability can allow us to recognize faces in uncontrolled crowds non-cooperative individuals can work with wider face angles. We own 8 patents just on these features.  

2019-07-15  Read More

FLEXIBLE OPEN ARCHITECTURE - AI-Powered Analytics In A Crowd

FLEXIBLE OPEN ARCHITECTURE

iOmniscient’s systems are designed to work in a way that suits your needs.

Our unique Artificial Intelligence Based Video Analytics Software will works with any camera, Distributed/ Edge or Centralized or Hybrid.

Any system that is implemented in a busy city must survive and operate over a long period of time. It must be adaptable to evolving needs as the technology and the expectations of its citizens change over the years. The system must therefore have a flexible architecture which protects the city’s investment in hardware over the next decade and longer.

The hardware and network architecture for a Smart City can be Centralized, Distributed or a hybrid of the two. Centralized architectures are suited to applications in which all the information needs to be captured and stored for future retrieval. There are applications, however, in which it does not make sense to store all the data as it may impose a heavy load on the network. Examples of these are situations in which megapixel cameras are used. In rare incidents, it makes sense to only store the high resolution images from certain incidents centrally. All other information can be stored in a low resolution format.

In these situations, the analysis can be done on a small computing device placed near or even inside the camera, known as computing at the Edge.

Since a city is a very distributed environment, at least a proportion of the surveillance would best be done on Edge devices. These are essentially little computers that sit inside or near the cameras (at the “edge” of the network). The traditional Edge devices that have been available to date just do not have the power to provide all the computing required. Hence, iOmniscient, in partnership with Intel, has built a Super Edge device which has the power to process the analytics for 4 cameras at a time in a rugged device.

 

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