EMBEDDED IOT ARCHITECTURE FOR FLOOD DETECTION AND VEHICLE SAFETY IN SUBMERGED UNDERPASSES

Flooded underpasses pose serious threats to vehicles and pedestrians, often leading to accidents during heavyrainfall. This project introduces an automated system designed to enhance safety in such conditions. The setupincludes water level sensors to detect flooding, a motorized gate to restrict entry, motion detection to identifyhuman presence near closed gates, and a drainage system that activates automatically. The entire process ismanaged through sensor-based logic without the need for remote communication or internet connectivity. Thesystem effectively prevents access, alerts individuals in danger, and removes excess water — offering a practical,low-cost solution for real-time flood management in urban area.but also pose serious threats to vehicle occupantsand pedestrians, sometimes leading to fatal accidents. Traditional warning systems are either manual or too slowto respond effectively in real-time conditions. To overcome these challenges, this project introduces an automatedflood safety and monitoring system that focuses on early action and physical prevention. The system employswater level sensors to detect flooding and activates a motorized gate to block entry when danger is detected. If aperson attempts to bypass the gate, a motion detection mechanism triggers an audible buzzer to alert them andnearby individuals. At the same time, a drainage motor is activated to remove excess water from the underpass,restoring it to safe conditions without manual intervention. This system provides a reliable, low-maintenance, andproactive solution to urban flooding issues, enhancing public safety through automation and real-time response.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-20
DOI
https://doi.org/10.5281/zenodo.15472006
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

EMBEDDED IOT ARCHITECTURE FOR FLOOD DETECTION AND VEHICLE SAFETY IN SUBMERGED UNDERPASSES

Zenodo (CERN European Organization for Nuclear Research)
Flood Risk Assessment and Management
article

EMBEDDED IOT ARCHITECTURE FOR FLOOD DETECTION AND VEHICLE SAFETY IN SUBMERGED UNDERPASSES

article en

Abstract

Flooded underpasses pose serious threats to vehicles and pedestrians, often leading to accidents during heavyrainfall. This project introduces an automated system designed to enhance safety in such conditions. The setupincludes water level sensors to detect flooding, a motorized gate to restrict entry, motion detection to identifyhuman presence near closed gates, and a drainage system that activates automatically. The entire process ismanaged through sensor-based logic without the need for remote communication or internet connectivity. Thesystem effectively prevents access, alerts individuals in danger, and removes excess water — offering a practical,low-cost solution for real-time flood management in urban area.but also pose serious threats to vehicle occupantsand pedestrians, sometimes leading to fatal accidents. Traditional warning systems are either manual or too slowto respond effectively in real-time conditions. To overcome these challenges, this project introduces an automatedflood safety and monitoring system that focuses on early action and physical prevention. The system employswater level sensors to detect flooding and activates a motorized gate to block entry when danger is detected. If aperson attempts to bypass the gate, a motion detection mechanism triggers an audible buzzer to alert them andnearby individuals. At the same time, a drainage motor is activated to remove excess water from the underpass,restoring it to safe conditions without manual intervention. This system provides a reliable, low-maintenance, andproactive solution to urban flooding issues, enhancing public safety through automation and real-time response.

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 60%
Flood Risk Assessment and Management
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