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• MODERN APPROACHES TO NATURAL FIRE MONITORING AND FORECASTING: REVIEW AND CONCEPT OF AUTONOMOUS UAV-BASED SYSTEM

  N.D. Boldyrev , V. V. Gilka , А.S. Kuznetsova , D.А. Morozov

  58-80

  2025-12-30

  Abstract ▼

  Natural fires cause serious damage to ecosystems, the economy, and public safety every year, and timely detection of fires and prediction of their development increases the speed of response to threats and allows for optimal allocation of resources during emergency response. Existing monitoring methods are limited by the speed of detecting fire outbreaks and the speed of their further spread, which reduces the effectiveness of rescue services. To solve this problem, heterogeneous data sources can be used, including unmanned aerial vehicles (UAVs), distributed sensor networks, mobile field observation systems, ground-based thermal imaging stations, etc., which can contribute to a more accurate analysis of the current situation and improve the reliability of predictive models of fire spread. The aim of the study was to develop a concept for an automated approach to monitoring and predicting wildfires based on unmanned aerial vehicles. We believe that this approach will improve the speed of detecting fire outbreaks and the accuracy of predicting their spread. The tasks include analyzing existing monitoring methods, developing a concept for a system that integrates multispectral imaging, optimized data transmission, automatic segmentation, and forecasting based on machine learning, as well as ensuring interaction between the operator and alert specialists. The work used methods of collecting, analyzing, and transmitting data from UAVs, processing multispectral images, machine learning and neural networks for fire detection, image segmentation algorithms and simulation modeling for fire spread prediction, data visualization to support decision-making by operators and administrators, logging and analysis of results for model training, software engineering, and human-computer interaction technologies. The system will reduce the time required to detect and predict fires, enable operators to launch multiple drones simultaneously, and automate the processing of data received from them. Process automation will reduce emergency response times and staffing levels, improve resource allocation, increase forecast accuracy, and improve the timeliness of emergency service notifications. This will help reduce damage from wildfires and improve the safety of people and ecosystems. Despite the progress made in addressing this challenge, the comprehensive system described in this article does not yet exist in its entirety in Russia, the CIS countries, or in Western and Asian countries. Although individual components, such as UAVs for monitoring and artificial intelligence (AI) for data analysis, are already in active use, there is currently no integrated solution that combines all elements (drone control, near real-time fire spread prediction, data transmission, and interaction with emergency services). does not currently exist. This concept represents a new approach that could become a breakthrough technology for combating natural disasters.

• TRANSFORMING THE DECISION-MAKING EXPERIENCE

  S. L. Belyakov, M. L. Belyakova, S.A. Zubkov, N.A. Golova, K.S. Yavorchuk

  2021-01-19

  Abstract ▼

  The problem of transferring the experience of decision-making in situational analysis using
  geoinformation systems is considered. The need for intellectual support from the geoinformation
  system is due to the fact that spatial objects and connections of the real world are extremely dynamic.
  Under these conditions, it is not possible to apply analytical models of processes and phenomena
  due to the incompleteness and inconsistency of the information describing them. Statistical
  models depend on a large number of factors, which vary as the geographical location of the
  situation changes. An alternative is to use the experience of experts who are able to make effective
  decisions in local spatial situations. The lack of control over the reuse of experience is a problem.
  The knowledge gained in developing solutions in one locality can lead to inadequate solutions in
  another locality. The experience of solving a problem in the same area loses its significance over
  time. In this paper, we propose a representation of knowledge in the form of an image consisting
  of a center and acceptable transformations of the center. Image transformation functions that
  perform knowledge transfer are introduced. The properties of transformation functions that carry
  procedural knowledge about the images of situations are analyzed. The use of the identified properties
  for the formation of a test plan for software transformation procedures is considered. Thecriteria for successful transformation are studied. The optimization problem of finding the best
  transformation function in the GIS knowledge base is formulated. A generalized method of transforming
  experience is proposed. An example of the synthesis of transformation methods for selecting
  an operational call center is given. The image of the situation of making a decision about
  choosing a land plot for a service center is transformed into the specified area on the GIS map.

• KNOWLEDGE FOR ARGUMENTATION IN COMPARISON OF SPATIAL SITUATIONS

  S.L. Belyakov, N.А. Golova, К.S. Yavorchuk, I. N. Rosenberg

  2022-05-26

  Abstract ▼

  The traditionally used way to assess the quality of the solution proposed by an intelligent
  system is to explain the course of logical inference. Knowledge about reasoning is used to argue
  the choice of a solution option. The sequence of applied rules, the facts used and the confirmed
  hypotheses are considered arguments that should convince the user of the validity of the formed
  conclusion. The disadvantage of this method of explanation is that it reflects a formally correct,
  but devoid of semantic content, course of reasoning. The argumentation of the solution obtained is
  based on the tracing protocol, which is essentially no different from debugging information when
  tracing programs. The argumentation in this case is far from the meaning of the situation. The
  meaning is understood as a given set of transformations of the situation that preserve the immutability
  of its perception by a human analyst. Knowledge about the semantic content of situations
  should be presented in a special fashion. In this paper, we consider a representation containing a
  precent and its permissible transformations. In this form, spatial situations in geoinformation systems
  are described. For argumentation, it is proposed to use special relations between images of
  situations. The concept of the area of applicability of the image is introduced. The mutual arrangement of the spatial-temporal and semantic shell of images and the areas of their applicability
  is considered as a carrier of the relationship. Information about relationships is extracted from the
  structure of the cartographic database. The relations of inheritance, aggregation, composition,
  generalization and association of classes of objects are considered. Knowledge for argumentation
  is provided by the rules for determining the reliability index of expert conclusion for individual
  relationships and their combinations. A method of automatic rule generation is proposed.
  The relations for comparison of levels of reliability of rules are given.

• INTELLIGENT RECOMMENDER SYSTEM FOR SPATIAL ANALYSIS

  S.L. Belyakov, А.V. Bozhenyuk, N.А. Golova, К.S. Yavorchuk, I.N. Rosenberg

  14-26

  2025-07-30

  Abstract ▼

  The work is devoted to the analysis of mechanisms of formation of recommendations and
  evaluation of the user's reaction to them in the interactive mode of work with the geoinformation
  system. One of the important areas of application of recommender systems is the search and decision-
  making in spatial situations. A peculiarity of this class of problems is the uncertainty of task definition and ambiguity of decision evaluation. Users are often faced with problems that do not
  have a clear formulation. To try to solve them, it is necessary not only to designate the direction of
  solution search, but also to find an adequate sequence of tasks with clearly formulated input and
  output data. Recommendations in such cases are designed in a dialogue with the user-analyst to
  develop a strategy for finding solutions. In this paper we study a smart recommendation system
  using the experience of dialog interaction. We propose a model of adaptation to the mental image
  of the problem, which builds the user, taking into account the levels of situational awareness and
  cognitive load. The peculiarity of the model is the use of visual cartographic objects, which are
  indicators of the state of the mental image. A recommendation is represented by a set of objects
  that are introduced into the field of cartographic analysis. This implicitly induces a certain semantic
  direction of increasing situational awareness. A criterion of satisfaction with the recommendation
  is suggested. A diagram of recommender system states, which describes the selection of context,
  adequate to the problem being solved, is given. The context is understood as an information
  object, capable of providing program functions and data for solving problems of a limited class.
  A sequence of contexts in an analysis session is considered as a precedent of experience. Indicators
  of trend, tendency and rhythm are proposed for possible chains of contexts. The degree of
  semantic proximity of precedents to the current course of search for a solution is estimated by
  these indicators. Their use will increase the speed of adaptation

• INTELLIGENT RECOMMENDER SYSTEM FOR SPATIAL ANALYSIS

  S.L. Belyakov, А. V. Bozhenyuk, N. А. Golova, К.S. Yavorchuk, I.N. Rosenberg

  14-26

  2025-07-31

  Abstract ▼

  The work is devoted to the analysis of mechanisms of formation of recommendations and
  evaluation of the user's reaction to them in the interactive mode of work with the geoinformation
  system. One of the important areas of application of recommender systems is the search and decision-
  making in spatial situations. A peculiarity of this class of problems is the uncertainty of task definition and ambiguity of decision evaluation. Users are often faced with problems that do not
  have a clear formulation. To try to solve them, it is necessary not only to designate the direction of
  solution search, but also to find an adequate sequence of tasks with clearly formulated input and
  output data. Recommendations in such cases are designed in a dialogue with the user-analyst to
  develop a strategy for finding solutions. In this paper we study a smart recommendation system
  using the experience of dialog interaction. We propose a model of adaptation to the mental image
  of the problem, which builds the user, taking into account the levels of situational awareness and
  cognitive load. The peculiarity of the model is the use of visual cartographic objects, which are
  indicators of the state of the mental image. A recommendation is represented by a set of objects
  that are introduced into the field of cartographic analysis. This implicitly induces a certain semantic
  direction of increasing situational awareness. A criterion of satisfaction with the recommendation
  is suggested. A diagram of recommender system states, which describes the selection of context,
  adequate to the problem being solved, is given. The context is understood as an information
  object, capable of providing program functions and data for solving problems of a limited class.
  A sequence of contexts in an analysis session is considered as a precedent of experience. Indicators
  of trend, tendency and rhythm are proposed for possible chains of contexts. The degree of
  semantic proximity of precedents to the current course of search for a solution is estimated by
  these indicators. Their use will increase the speed of adaptation.