The solution is designed for software solutions in indusry and public management.
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
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:
Incoming message formats, rules and algorithms for message processing, formulas for calculating key indicators, methods for recognizing typical situations, predictive models, descriptions of forces and means are developed as part of models of each subject area (type of activity) described in COSOC sets of xml files. COSOC is built on the basis of a service-oriented architecture, the main element of which is an Integration Platform for interaction with external data sources, as well as related systems. Information from CAP messages is extracted in accordance with the exchange regulations, grouped, if necessary, after which it is processed according to algorithms and methods previously laid down in COSOC at three hierarchical levels, in accordance with the IBM Component Business Model proposed: 1) the level of direct response to the event; 2) the level of tactical decision-making on situations; 3) the level of strategic decision-making. Incoming information is processed
To ensure calculations, algorithms and working methods, the following information support is provided in COSOC:
1. A directory of CAP messages, including a description of message types and codes, a list of external sources linked to these types of messages.
2. A directory of external sources of messages, including a description of the types of sources, as well as parameters of the protocols of exchange with them, including methods of constructing requests to them and characteristics of the generated requests.
3. The KPI classifier, which describes, in fact, the model of the subject area, including, among other things, algorithms for calculating KPI, threshold values.
4. A codifier of typical tactical situations containing a list of typical tactical situations, a list of KPI values, single and group CAP messages by which the situation can be recognized, a list of requests for additional information from external sources (or manually entered), as well as formalized criteria for evaluating the entire set of parameters.
5. A register of Response Plans containing a detailed list of measures for each Plan, linked to the Forces and Means that are involved in their implementation.
6. Directory of Critical Infrastructure Objects, including a passport of the object indicating the geographical coordinates of the location of the object;
7. A directory of types of Forces and Means containing descriptions of the types of resources, both human and technical, that are involved in the implementation of Action Plans.
8. Passports of Forces and Means describing the real situation with the availability and arrangement of resources, according to the Directory of Forces and Means.
9. Technical conditions (technical specifications) for the interaction of external data sources and related systems, which regulate the exchange of information.
Хельвас А.В., Овчинников А.Д., Кузнецова А.А., Гиля-Зетинов А.А.
в сборнике ”Имитационное и комплексное моделирование морской техникии морских транспортных систем” Материалы пятой международной научно - практической конференции ИКМ МТМТС-2019, место издания М: ”Издательство Перо”, с. 191-196
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.
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.
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.