Орман өрттерін бақылауда ұшқышсыз ұшу аппараттарының деректерін өңдеу үшін Python бағдарламаларын пайдалану.
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| Název: | Орман өрттерін бақылауда ұшқышсыз ұшу аппараттарының деректерін өңдеу үшін Python бағдарламаларын пайдалану. (Kazakh) |
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| Alternate Title: | Using Python programs to process data from unmanned aerial vehicles for forest fire monitoring. (English) Использование программ Python для обработки данных беспилотных летательных аппаратов для мониторинга лесных пожаров. (Russian) |
| Autoři: | Молдамурат, Х., Калманова, Д., Базарбек, А., Атанов, C. К., Ырыскелді, Н. |
| Zdroj: | Bulletin of the L.N. Gumilyov Eurasian National University. Technical science & Technology series; 2025, Vol. 153 Issue 4, p139-151, 13p |
| Témata: | FOREST fire management, GEOGRAPHIC information systems, DRONE aircraft, DATA visualization, DATA mining, ENVIRONMENTAL security, PYTHON programming language, COMMERCIAL drones |
| Abstract (English): | Modern challenges to environmental safety require the integration of engineering and information technologies to quickly respond to threats such as forest fires. One promising area is the use of unmanned aerial vehicles (UAVs) in combination with geographic information systems (GIS) and data mining software. In this paper, we consider a project to create a software solution implemented in Python for monitoring and predicting the spread of forest fires. 3,000 hectares of woodlands divided into sectors were used as a conditional landfill. Each sector was analyzed based on weather data (temperature, humidity, wind speed), vegetation density, and fire hazard index calculations. The libraries Folium (for interactive mapping), Pandas (for tabular data processing) and Matplotlib (for visualization) were used for implementation. Three drones (multispectral camera, thermal imager, RGB camera), equipped with various sensors, worked on a schedule, providing continuous monitoring based on charging time. The proposed architecture of the system makes it possible to adapt it to various geographical conditions and tasks. The results are presented in the form of graphs, heat maps and tables, which makes the system convenient for operators and analysts. The work is relevant in the field of "Engineering and Technology" and reflects the synthesis of information and engineering solutions to environmental safety problems. [ABSTRACT FROM AUTHOR] |
| Abstract (Russian): | Современные вызовы природной безопасности требуют интеграции инженерных и информационных технологий для быстрого реагирования на такие угрозы, как лесные пожары. Одним из многообещающих направлений является использование беспилотных летательных аппаратов (БПЛА) в сочетании с географическими информационными системами (ГИС) и программным обеспечением для интеллектуального анализа данных. В данной работе рассматривается проект создания программного решения, реализованного на языке Python для мониторинга и прогнозирования распространения лесных пожаров. В качестве условного полигона использовались 3000 га лесных массивов, разделенных на секторы. Каждый сектор был проанализирован на основе данных о погоде (температура, влажность, скорость ветра), плотности растительности и расчетов индекса пожарной опасности. Для реализации использовались библиотеки Folium (для интерактивного картографирования), Pandas (для обработки табличных данных) и Matplotlib (для визуализации). Три дрона (мультиспектральная камера, тепловизор, камера RGB), оснащенные различными датчиками, работали по расписанию, обеспечивая непрерывный мониторинг с учетом времени зарядки. Предлагаемая архитектура системы позволяет адаптировать ее к различным географическим условиям и задачам. Результаты представлены в виде графиков, тепловых карт и таблиц, что делает систему удобной для операторов и аналитиков. Работа актуальна в рамках направления" Инженерия и технология " и отражает синтез информационных и инженерных решений задач экологической безопасности. [ABSTRACT FROM AUTHOR] |
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| Databáze: | Complementary Index |
Nájsť tento článok vo Web of Science | Abstrakt: | Modern challenges to environmental safety require the integration of engineering and information technologies to quickly respond to threats such as forest fires. One promising area is the use of unmanned aerial vehicles (UAVs) in combination with geographic information systems (GIS) and data mining software. In this paper, we consider a project to create a software solution implemented in Python for monitoring and predicting the spread of forest fires. 3,000 hectares of woodlands divided into sectors were used as a conditional landfill. Each sector was analyzed based on weather data (temperature, humidity, wind speed), vegetation density, and fire hazard index calculations. The libraries Folium (for interactive mapping), Pandas (for tabular data processing) and Matplotlib (for visualization) were used for implementation. Three drones (multispectral camera, thermal imager, RGB camera), equipped with various sensors, worked on a schedule, providing continuous monitoring based on charging time. The proposed architecture of the system makes it possible to adapt it to various geographical conditions and tasks. The results are presented in the form of graphs, heat maps and tables, which makes the system convenient for operators and analysts. The work is relevant in the field of "Engineering and Technology" and reflects the synthesis of information and engineering solutions to environmental safety problems. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 26167263 |
| DOI: | 10.32523/2616-7263-2025-153-4-139-151 |