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All Journal International Journal of Evaluation and Research in Education (IJERE) Computer Science and Information Technologies
Kalmanova, Dinara
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Computer Science & IT Education Engineering

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Geoinformation system for monitoring forest fires and data encryption for low-orbit vehicles Moldamurat, Khuralay; Bakyt, Makhabbat; Yergaliyev, Dastan; Kalmanova, Dinara; Galymzhan, Anuar; Sapabekov, Abylaikhan
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p58-67

Abstract

This article discusses two important aspects of unmanned aerial vehicles (UAVs): forest fire monitoring and data security for low-orbit vehicles. The first part of the article is devoted to the development of a geographic information system (GIS) for monitoring and forecasting the spread of forest fires. The system uses intelligent processing of aerospace data obtained from UAVs to timely detect fires, determine their characteristics and forecast the dynamics of development. The second part of the article focuses on the problem of high-speed encryption of data transmitted from low-orbit aircraft. An effective encryption algorithm is proposed that ensures high data processing speed and reliable protection of information from unauthorized access. The article presents the results of modeling and analysis of the effectiveness of the proposed solutions.
Active online learning with remote sensing data in higher education Moldamurat, Khuralay; Atanov, Sabyrzhan; Nagymzhanova, Karakat; Spada, Luigi La; Kalmanova, Dinara; Tazhikenova, Sapiya; Zhanzhigitov, Syrym; Zhakupov, Altynbek; Yessilov, Assylkhan; Bakyt, Makhabbat
International Journal of Evaluation and Research in Education (IJERE) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v14i3.30096

Abstract

The increasing popularity of online learning has created a need for effective methods to enhance educational quality. This study addresses this need by developing and evaluating an active online learning model incorporating remote sensing data (RSD). The study included a pedagogical experiment with 181 students divided into control and experimental groups. The model included an interactive database, a web portal with tools for processing and visualizing RSD, and the implementation of active learning methods. Data were collected through testing, analysis of completed projects, and questionnaires. Quantitative and qualitative analysis methods were used to process the data. The pedagogical experiment showed that the model improved students’ average scores, increased the number of students with high levels of knowledge acquisition, and enhanced motivation. Thus, the use of RSD and active learning methods in online education is a promising approach to improve the quality of the educational process and foster students’ digital competence.
Co-Authors Atanov, Sabyrzhan Bakyt, Makhabbat Galymzhan, Anuar Moldamurat, Khuralay Nagymzhanova, Karakat Sapabekov, Abylaikhan Spada, Luigi La Tazhikenova, Sapiya Yergaliyev, Dastan Yessilov, Assylkhan Zhakupov, Altynbek Zhanzhigitov, Syrym