Published on: June 2026
AIOT-ENABLED MACHINE LEARNING SYSTEM FOR REAL-TIME FLASH FLOOD PREDICTION AND EARLY WARNING IN RURAL AREAS
GAIKWAD SAGAR KALYANRAO
Wagholi, Pune-412207
Article Status
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Abstract
Floods are among the most devastating natural disasters, causing significant loss of life, damage to infrastructure, agricultural destruction, and economic disruption across the world. Among various types of floods, flash floods are particularly dangerous because of their sudden occurrence, rapid development, and limited response time. In recent years, factors such as climate change, extreme rainfall events, environmental degradation, deforestation, and changing land-use patterns have contributed to the increasing frequency and severity of flash floods, especially in rural and geographically vulnerable regions.
Rural communities are highly susceptible to flash flood disasters due to inadequate monitoring infrastructure, poor communication facilities, and limited access to advanced disaster management technologies. These floods often result in loss of human lives, crop damage, destruction of public infrastructure, and long-term socio-economic impacts. Therefore, the development of efficient flood prediction and early warning systems has become essential for improving disaster preparedness and community resilience.
How to Cite this Paper
KALYANRAO, G. S. (2026). AIoT-Enabled Machine Learning System for Real-Time Flash Flood Prediction and Early Warning in Rural Areas. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(6). https://doi.org/10.55041/ijcope.v2i6.323
KALYANRAO, GAIKWAD. "AIoT-Enabled Machine Learning System for Real-Time Flash Flood Prediction and Early Warning in Rural Areas." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 6, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i6.323.
KALYANRAO, GAIKWAD. "AIoT-Enabled Machine Learning System for Real-Time Flash Flood Prediction and Early Warning in Rural Areas." International Journal of Creative and Open Research in Engineering and Management 02, no. 6 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i6.323.
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- •Published on: Jun 25 2026
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