The paper proposes the conceptual foundations of robotization of serial engineering equipment designed for emergency rescue and other urgent work. The relevance of this approach to extreme robotics is caused by the frequent failure of prototypes of robotic tools and the lack of sufficient funds for their repair, which ultimately does not allow the full use of the existing fleet of automatic devices for fire and rescue and other urgent work. The system of a mobile remotely controlled complex for robotizing serial equipment intended for emergency rescue and other critical work is considered. The developed system is based on optical methods of control and recognition of objects.
From the point of view of satellite monitoring, construction objects include fixed objects of artificial origin (buildings and structures for various purposes), created from building materials and lying directly on the earth's surface. Someone can conditionally divide the life cycle of a construction object into initial, main and final stages. From the point of view of satellite, ground, aerial photography it is possible to distinguish building objects at the initial, main and final stages from each other. In this case, not all initial stages are exposed to the images, and additional conditions are required to distinguish the final stages in the images (the same applies to the main stages). We can produce the current stage of the life cycle of a building object for various reasons. The paper considers some features of deciphering construction objects at the initial and final stages of their life cycle, primarily in an emergency and abandoned state. Relevant types of construction objects are identified, the structure of decoding signs is determined, and decoding areas are established, we derive the signs themselves for different construction objects. An experiment on the detection of abandoned construction sites on several databases is given.
Remote sensing is an objective monitoring of the dynamics of changes in the resource potential of the tourism component of the country's modern economy. This paper proposes the information storage model for creating a global space monitoring system for the presence of municipal solid waste objects with elements of economic analysis and recreation of the health of potential tourists and the ecology of recreational areas around the world. The proposed model uses methods for decoding remote sensing images by fractal-percolation image analysis and elements of convolutional neural networks. The purpose of the work is to design a model of a global automatic monitoring system for waste disposal facilities, including industrial ones, using Earth remote sensing technologies in recreational areas, followed by an economic analysis to reduce the resource potential in the tourism business in the face of deteriorating ecology of the studied areas.
The paper describes an approach to restoring a three-dimensional model of rigid objects from a single satellite image based on informative classes identified from the results of machine learning, which include railway rails and poles, roofs and walls of buildings, shadows of poles and buildings, and others. The proposed algorithms take into account various conditions for the presence of certain classes in the image, identified by the results of machine learning, as well as the conditions for the absence of metadata on the spatial resolution and spatial orientation of the shooting and the Sun (shooting angle, scanning azimuth, etc.).
This study presents a remote sensing application of using time-series satellite images for monitoring the solid waste disposal facilities (WDF). Solid waste management and monitoring is a critical issue for the metropolitan authorities of developed and developing countries. This is due to the appearance of natural, unauthorized garbage dumps that negatively affect the ecological and epidemiological state of the environment. It is advisable to solve this problem remotely, using remote sensing technologies, having high-and medium-resolution information from spacecraft. We propose a method of filtrate analysis and space images (SI) decryption are carried out with the use of a DOT apparatus and, in particular, with the use of Viner filtering. In this work, Winer filtering is used, as part of the proposed algorithm of computer simulation of the fractal-percolation process of filtrate of the underlying surface of WDF, the filtering threshold is determined, as well as studies for correctness on Tikhonov are carried out. The experiment is carried out on the example of a SI with a WDF image. An extension of the feature space is also modeled using stochastic geometry. The results obtained can serve as a basis for the development of a methodology for assessing the effectiveness of measures to neutralize the underlying surface of the WDF from the filtrate and leak it into the soil using remote sensing of the Earth technologies. This methodology can be the subject of further research on the development of a medical and preventive expert system at the territorial level for the detection and neutralization of unauthorized WDFs on medium and high-resolution space images.
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