CrossTech DataNova OR (Object Recognition)

Main articles:

• Computer vision (machine vision)
• Video analytics (terms, applications, technologies)
• Biometric identification technologies
• Facial recognition systems

DataNova OR (Object Recognition) is a solution developed by CrossTech Solutions Group. Product functionality is based on computer vision technologies. This tool allows you to monitor the activities of remote employees by intercepting a video stream from a webcam and detect illegitimate activity according to a configured security policy and block the workstation.

2022: Objectives and main functions

According to information for March 2022, DataNova OR proposes to solve the following problems:

• Implementation of logic to intercept video stream from the device webcam;
• Training of neural networks and implementation of logic on object recognition on video stream;
• Automatic locking of AWS in case of incident detection;
• Centralized collection of recognition results and recorded incidents and deviations;
• Automation of management and application reporting.

Basic functions

You can use the OR DataNova to solve the following queries:

• Capturing images from the device's webcam;
• Identification of different objects on the video stream using computer vision technologies;
• Identify attempts to photograph the screen, drink alcohol and other illegitimate actions according to security policy;
• Ability to configure security policies to detect illegitimate activity and lock the workstation;
• Support mechanisms for developing user-defined correlation/anomaly rules;
• Automatically captures images from a virtual webcam;
• A neural network that allows you to recognize more than 80 different objects;
• Using Advanced Facial Recognition Algorithms

What are the results of the OR DataNova:

• Automation of mechanisms to detect illegitimate actions of employees;
• Increased objectivity and awareness of remote staff;
• Improving the efficiency of remote employees;
• Identification of illegitimate persons outside the AWS and/or identification of absence of the employee behind the workplace during working hours;
• Implementation of real-time monitoring of employee activities.