Modern technologies for monitoring waterlogged areas and their impact on infrastructure

2025

Полный текст Открытый доступ: Gold Метаданные (CSL-JSON)
DOI 10.32523/2616-7263-2025-150-1-226-248
Достоверность данных 70 средняя
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Складывается из проверяемых признаков самой записи: есть ли у статьи DOI, сколько независимых источников подтвердили её данные, заполнены ли обязательные поля и насколько свежо последнее подтверждение. Снижают оценку расхождения между источниками и отсутствие идентификатора. Значение от 80 означает, что запись опубликована без дополнительной проверки; от 60 до 79 — что она опубликована с пониженной достоверностью и ручная проверка желательна. Запись, выверенную редактором вручную, пересчёт не опускает ниже 90. Это оценка наших данных о статье, а не оценка самой статьи.

Аннотация

This review article analyzes modern technologies for monitoring waterlogged areas and their impact on infrastructure. The specificity of considered articles led to determining 5 main categories that formed the structure of the review, including water management and infrastructure solutions; data-driven monitoring and forecasting; Internet of Things (IoT); airborne and mobile technologies; analytical and computational methods. When selecting articles for review, those that offer modern solutions had an advantage, including Geographic Information Systems (GIS), Remote Sensing (RS), IoT, Unmanned Aerial Vehicles (UAV), Machine Learning (ML), and Artificial Intelligence (AI). An analysis of these solutions has been carried out and their disadvantages have been identified. The review revealed the integrated solutions provide more efficient and accurate real-time monitoring, prediction, and detection of waterlogged areas. The review highlights the importance of integrating various modern technologies to create more efficient and accurate systems for monitoring, predicting risk zones, and detecting waterlogged areas. Particular attention is paid to the application of integrated solutions such as the use of UAV with AI for flooded area estimation, IoT with AI for real-time water level monitoring, and ML with AI for flood risk prediction. An analysis of publications over the last 10 years shows a significant increase in interest in these solutions due to the increasing relevance and difficulty of waterlogging problem solutions in the face of climate change, urbanization, and extreme weather events. It is predicted that in the future such approaches will play a key role in the development of flood risk management strategies, protecting populations and infrastructure.