The process describes an intelligent system creation designed for risk evaluation and management. The risk can be anthropogenic, natural, or social nature, and belong to territories of diferent scales. Complexity in structuring and collecting information about the state territorial security as well as diferent risks assessment methods necessitate the development of a modular multitask system. The information management system support model formalizes the problem area to justify the joint intelligent technologies use. Based on the model, system architecture has been developed. This architecture defines the composition, functionality, interaction interfaces, as well as the information resources organization, that were used to support management. Here is presented an intelligent system prototype operation result.
Maintaining the territorial safety is a challenging task, especially when the economy fails.
However, existing technologies readily provide an opportunity to implement low-cost measures
allowing to manage social, natural, and technogenic risks. It is important to study various
territorial characteristics, treating them as complex systems, in order to find and justify these
measures. One of the most theoretically well-supported concepts is the idea of the territory
as a complex socio-natural-technogenic system where multiple risk groups are formed and
implemented [
In order to establish acceptable various risks’ levels for conducting a sociological survey, a
risk classification was carried out as part of the iNTeg-Risk project [
To control territories in the EU countries, the concept of “smart city” or “smart territory”
based on the criteria for sustainable and efective development is actively being developed. This
concept covers various spheres of life: energy, transport infrastructure, resource consumption,
environmental impact, etc. It requires a detailed analysis and diagnosis of the territory and key
indicators to create such a system [
The results obtained by the researches [
This work proposes the “end-to-end” technology creation for designing and building an intellectual system responsible for assessing territorial risks. It briefly describes the contents of the informational support systemic model for territorial risk management, which underlies the architecture of the intellectual system. The presented architecture allows you to create multitask problem-oriented systems; some of them are already implemented in the Siberian region.
The result of the first stage building an intelligent system is a management support system
model M that formalizes the basic requirements, composition and elements interaction in the
form [
= ⟨, , , , , , ⟩, where — management objectives; — control tasks; — decision levels; — system functions; — containers integrating information resources, their processing methods and characteristics for each type of risk; — information technologies; — formed decisions. The listed elements of the model are detailed as sets.
Management goals set = {1, 2, 3} include: 1 — increase life expectancy by reducing
the number of dead and deceased prematurely; 2 — increase in the healthy life duration
by reducing the number of people who need treatment, rehabilitation and social protection;
3 — comfortable living environment creation, including the environment normalization and
uninterrupted resources supply. All management goals have a multiplier efect — financial
investments in preventive measures are significantly less than the cost of unprevented harm [
Containers in an intelligent system are presented as pairs = {, }, where —
information resources, — methods and algorithms that process and present data using information
technologies [
Let us focus on the description of knowledge bases. Their structure in a generalized form
reflects the representation of a multilevel aggregated knowledge model used in the solving
control problem process and described in [
Integrating these technologies in control systems allows synthesizing solutions that coordinate the actions of experts from various departments involved in the targeted risk reduction programs development. Updated information resources increase the decision efectiveness when it comes to working with lack of time, the presence of incomplete and obscure initial information, and the error high costs.
The intelligent system work results largely depend on the volume and content of the data,
which is diferent for diferent territories. The output can be represented as = {, , , },
where — text recommendations and explanations; — tables; — graphical representations;
— dynamic maps visualizing the territorial risks distribution. For a better understanding,
includes the extensive terminology used in risks assessment [
Elements from sets of this system model can be supplemented with the new data processing technologies advent, information resources types, as well as territorial management tasks.
The next step in the intelligent system implementation is architectural design, linking the system model elements, and the information processes decomposition of the system’s interaction with the external environment, and the program modules functioning within the system.
The multitasking problem-oriented intelligent system architecture is based on the system management model. Figure 1 shows context diagram of the system interacting with the environment. This configuration allows getting results when performing various combinations of functions . For example, 1 data collection results and consolidation are available to other systems through a data gateway. Performing risk assessments (functions 2, 3) without forming solutions 4 is advisable in case of information resources deficiency.
Using the control support model elements, control tasks were decomposed as functional diagrams. This allowed describing in detail the transformation processes of information resources using IT technologies. The architecture concretizes the intelligent system design describing a unit of consolidating information resources, subsystems and data processing services, and human-machine interfaces (Figure 2).
Consolidation processes are described in accordance with the classification of information
resources and information technologies introduced in the system model. The use of
systemforming resources d1 to enrich monitoring data during the consolidation process in the
repository made it possible to implement various analytical processing technologies, such as POD
(post OLAP dynamics), Data Mining, and others [
Due to significant diferences in the data structure, processing and presentation result methods, it is advisable to integrate them for each risk type by the type of container processing. The growth of intellectualization system is possible with the mass knowledge bases formation that describes the preventive measures management processes. A graphical interface is being developed to transform formalized descriptions of multi-step actions. The large training sample formation makes it possible to use neural networks and other intelligent technologies. This allows creating several alternative solutions with ranking them by priority.
Human-machine interfaces are designed taking into account diferent decision-making levels . Diferent dynamic representations of the processing results (elements of the set ) allow avoiding the reduction of risk assessments as a single numerical indicator. The support includes various access mechanisms for individuals who form and make managerial decisions — desktop software systems, websites, and mobile applications.
The developed architecture made it possible to determine the synthesized intelligent system functionality and substantiate the software components and rational methods choice for the integrated control problems solution.
To assess territorial risks, it is proposed to collect and analyze monitoring data and statistics on
emergencies and dangerous events, including industrial safety violations, public health, and
environmental monitoring data. The proposed approach diference is using formalized
characteristics of the danger sources, objects’ vulnerability, and the state of protection systems [
The territorial risks assessment takes place in three main stages: — definition and formation of a source data array; — risks calculations and analytical modeling; — analysis results dynamic presentation, including risks mapping.
During the first stage, there are determined possible dangers for the territories, initial data, general target information and models for the analytical risks study are formed. When performing the second stage, it is necessary to divide the risks into two fundamental groups, characterized by the exposure duration (instant and long-term efect). At the third stage, recommendations are developed for risk management at the municipal level.
The risk calculation is carried out in order to determine the necessity and efectiveness of preventive measures, as well as measures to manage the municipality’s developmental risks by executive authorities.
The architecture’s basic functions are implemented in the integrated management support
systems “ESLA-PRO” and the Risk Analysis System SAR ES. Operational experience has shown
the necessity to improve intersystem information exchange using distributed ledger technologies,
cloud data storage, consolidating information from industry systems. Also have been created
updated regional atlases of emergency situations covering natural and anthropogenic natures,
some of them are published on the ICM SB RAS [
The proposed creation method of an intelligent system for assessing and managing social,
natural and anthropogenic systems’ risks allows building up a comprehensive information
platform for solving a wide range of territorial management tasks. The method is based on the
management information support model and the intelligent system architecture that substantiate
the original integration of information resources and technologies. The combination of an
intelligent system with integrated monitoring services will systematically reduce the human and
social life risks, as well as the ecological systems’ state to acceptable values that are currently
achieved in only a small number of countries [
This research project No. 18-47-240006: “Methods and information technologies for risk assessment of the development of socio-natural-technogenic systems in an industrial region” was funded by the Russian Foundation for Basic Research, Government of Krasnoyarsk Territory, Krasnoyarsk Regional Fund of Science.