Central regions | Technology & innovation

New AI system identifies employees' psychoemotional state

27 Jul '21
The Russian company iPavlov has developed a system based on artificial intelligence that recognizes deviations in the psycho-emotional state of a person in real time. The spectrum of conditions that the AI ​​can detect includes alcohol intoxication, anxiety, aggression, and other employee disorders.

The system will be able to transmit data in a timely manner to the dispatch office of the enterprise security service. It will help companies improve their efficiency, reduce workplace injuries, combat theft, and improve worker satisfaction. The project will be presented at the intensive Archipelago 2121 in Veliky Novgorod, the press service of the NTI Platform reports.

A team of developers iPavlov and SIC Shvabe is working on a project at the NTI Competence Center in the field of Artificial Intelligence at the MIPT. The state of the employee is determined by the AI ​​using photo and video data analysis. The system is compatible with almost any camera that customers use.
“A “map” is built on the face from points that are significant for determining the emotions experienced, which are combined into geometric shapes and separate groups of points - markers, the movement of which is monitored by algorithms. By analyzing the distance from the center of the face to the marker, the distance between the markers and their changes, the algorithm predicts what emotion a person is experiencing at the moment. Simply put, these markers often represent signs of emotion that are visible to the human eye, for example, folds on the forehead as an expression of anger or surprise,” says Laurent Hakobyan, General Director of iPavlov, Director of Applied Software Development at the NTI Competence Center in the direction of Artificial Intelligence.
In addition, the AI ​​will be able to analyze the voice by its intensity, volume, pause length and other parameters. For example, happiness can be expressed in shorter periods of constant pitch, and long, intense speech is indicative of negative emotions being experienced. The analysis of the employee's condition takes a maximum of 5 seconds. The system was trained on data from both open sources and closed tagged datasets.

The developers see as potential customers enterprises that extract valuable minerals, metals and other resources, as well as processing companies. With the help of the new system, it will be easier for the employer to control the working environment within the enterprise. The project can be finalized according to customer requests.

At the 2121 Archipelago, the team expects to find investors and customers, as well as receive additional expertise.
“There is no exact information on the current volume of the emotion detection and recognition market in open sources, but in 2017 it was just over 280 million rubles and had a dozen participants. Our company wants to occupy about 30% of this area in Russia,” the team representatives say.
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