26 Jun IDIS launches AI in the Box solution with industry beating accuracy rates
IDIS has launched its AI in the Box (DV-2116) boosting the power of surveillance systems with what it says are the most accurate deep learning analytics yet developed. The Korean surveillance manufacturer says in independent tests IDIS Deep Learning Analytics (IDLA) has achieved industry-beating accuracy rates of 97%, a record performance which is further boosted by high speed processing.
According to IDIS, The DV-2116 makes deep learning analytics more affordable for small to mid-sized applications, enhancing security and control room efficiency. The plug-and-play IDLA-ready appliance comes embedded with an NVDIA GTX1060 GPU chipset allowing the analysis of up to 16 channels simultaneously. Users benefit from robust and calibration-free object detection and classification (objects such as people, cars, and bicycles); intrusion and loitering detection; powerful, intelligent search functions and tracking by colour, object and number.
James Min, managing director, IDIS Europe, says this latest innovation has the potential to make surveillance much less labour intensive and more effective for a wide range of users.
“Our high accuracy analytics can process vast amounts of data, without a break, in a way that human operators can’t. This means that high-resolution video streams can be automatically monitored to spot suspicious behaviour or distinguish potential threats from every day activity.”
IDIS’s Deep Learning Engine, which powers the new AI in the Box solution, can recognise potentially significant movements and characteristics of people and vehicles, while ignoring activity that isn’t relevant. The technology can quickly check through hours of video to find specific individuals. It also becomes more accurate over time due to its self-learning characteristics.
“This is very exciting as it means that time critical activities – such as investigating incidents – will become increasingly efficient as our analytics are embedded in operations,” adds James Min.