Purpose of the solution

The solution is designed for software solutions in indusry and public management.  

Functions of COSOC.BG

receiving and recording messages from subjects (various DDS, utilities, citizens, etc.) and objects (SCADA systems, video cameras, etc.) in a centralized or decentralized storage;

displaying information about messages both on the map base and in the list (news feed) in accordance with the selected rules;

processing messages according to pre-configured algorithms and rules; calculation and display of key indicators describing the current situation in the areas of activity of the monitoring object;

recognition and assessment of the current situation based on the received messages; selection of the proposed response plan based on the accumulated database;

modeling of the current situation (simulation, dynamic, etc.) with the possibility of answering the question "What will happen if" and "What would happen if";

formation of a database of response plans; displaying the location of critical infrastructure objects, forces and means on the map base;

displaying the general picture of the situation of a specific situation

Data Sources

Information about events and threats comes from external sources (subjects or objects) in the Common Alerting Protocol (CAP, General Alert Protocol) format. CAP is an xml format supported by the Organization for the Development of Structured Information Standards (ORSSI), as well as defined in Recommendation ITU-T X.1303.

As sources of information can be used:

• mobile devices that allow citizens to report events and threats; stationary devices "alarm button";
• serviced and unattended sensor systems (transport, meteorological, environmental, special...);
• intelligent video surveillance systems; dispatcher services on duty;
• external systems that transmit information through interdepartmental communication channels (including international ones);
• mass media, telegraph agencies; public services.

Event-driven solution for operation center on the base of Common Alerting Protocol

Konstantin Zhigunov,   Evgeniya Tsybulko,   Alexander Khelvas

The article proposes the architecture of the Common Alerting Protocol based solution for event-driven Emergency Operation Center for regions of the Russian Federation. Sources of information are analyzed and approaches to tactical situations detection and estimation are discussed.

The software platform and information model of a situational center

S.S.Shcherbakov, A.A.Kuznetsova, A.A.Bespalko, A.S.Galitskiy,  A.V.Khelvas

Trudy MFTI 2018 v.10 №4(40) pp.98-109

The article deals with message standards for transmitting information on emergencies and a software platform for sharing them between government agencies and the full range of organizations related to emergencies.

Practical usage of Alloy for tactical situations recognition

A.V. Khelvas, A.B. Galitskiy

Trudy MFTI 2018 v.10 №4(40) pp.87-97

The article discusses the approach to the detection of tactical situations based on the analysis of formal statements generated by processing the flow of messages about events and threats in a formalized form in the software platform of the operation center . The analysis uses the Alloy language and the Alloy Analyzer analytical application. An example of an analysis for the typical flood threat detection situation is also discussed.

Improved 2D Human Pose Tracking Using Optical Flow Analysis

Khelvas Aleksander, Gilya-Zetinov Alexander, Konyagin Egor, Demyanova Darya, Sorokin Pavel, Khafizov Roman in book Advances in Intelligent Systems and Computing, series AISC, Springer, v. 1100, pp. 10-22   DOI: 10.1007/978-3-030-55187-2_2 In this paper, we propose a novel human body pose refinement method that relies on an existing single-frame pose detector and uses an optical flow algorithm in order to increase quality of output trajectories. First, a pose estimation algorithm such as OpenPose is applied and the error of keypoint position measurement is calculated. Then, the velocity of each keypoint in frame coordinate space is estimated by an optical flow algorithm, and results are merged through a Kalman filter. The resulting trajectories for a set of experimental videos were calculated and evaluated by metrics, which showed a positive impact of optical flow velocity estimations. Our algorithm may be used as a preliminary step to further joint trajectory processing, such as action recognition.