Ключевое слово: «environmental monitoring»

This work focuses on the development of an Arduino-based data logging and storage module that is relevant to the development of Internet of Things (IoT) applications. The main objective is to create a device that can record and archive data only when it changes, thereby increasing its effectiveness for environmental monitoring and automation of automation processes. The research includes the study of Arduino microcontroller operating principles, data logging methods and existing solutions in this field. The results obtained show that the developed data logger is effective and applicable in various IoT projects. This work contributes to the understanding of data management in IoT systems by implementing efficient data logging solutions.

The assessment of environmental conditions using satellite imagery processing remains a crucial area of scientific research, particularly in monitoring vulnerable Arctic regions. This study focuses on evaluating the impact of forest fires near the village of Bias-Kyuel in Yakutia using satellite imagery processing technologies. The research employs Sentinel-2 satellite imagery analysis and the Normalized Difference Vegetation Index (NDVI) as its primary method, examining data from July 18 to August 17, 2021, to assess vegetation changes before and after major forest fires. Through the processing and analysis of Red (B04) and NIR (B08) spectral bands with WGS 84 (EPSG:4326) coordinate system and resolution of 0.0000808 degrees per pixel in latitude and 0.0001766 degrees per pixel in longitude, the study created a detailed mask of burned areas. The analysis revealed significant NDVI value decreases in affected regions, with the total burned territory calculated at approximately 412 square kilometers. The study demonstrates the effectiveness of satellite imagery processing methods in quantifying environmental damage and monitoring ecosystem changes in remote Arctic regions.