ArticleSensors (Basel, Switzerland)2022
An Integrated Artificial Intelligence of Things Environment for River Flood Prevention.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Development of an AIoT-Based Early Flash-Flood Warning System for Smart Rural Disaster Resilience.Sensors (Basel, Switzerland) · 2026Article
- Leveraging artificial intelligence in disaster management: A comprehensive bibliometric review.Jamba (Potchefstroom, South Africa) · 2025Article
- A Review of Cutting-Edge Sensor Technologies for Improved Flood Monitoring and Damage Assessment.Sensors (Basel, Switzerland) · 2024Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
River floods are listed among the natural disasters that can directly influence different aspects of life, ranging from human lives, to economy, infrastructure, agriculture, etc. Organizations are investing heavily in research to find more efficient approaches to prevent them. The Artificial Intelligence of Things (AIoT) is a recent concept that combines the best of both Artificial Intelligence and Internet of Things, and has already demonstrated its capabilities in different fields. In this paper, we introduce an AIoT architecture where river flood sensors, in each region, can transmit their data via the LoRaWAN to their closest local broadcast center. The latter will relay the collected data via 4G/5G to a centralized cloud server that will analyze the data, predict the status of the rivers countrywide using an efficient Artificial Intelligence approach, and thus, help prevent eventual floods. This approach has proven its efficiency at every level. On the one hand, the LoRaWAN-based communication between sensor nodes and broadcast centers has provided a lower energy consumption and a wider range. On the other hand, the Artificial Intelligence-based data analysis has provided better river flood predictions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.