LiFi In Disaster Management: A Case Study Of Dam Monitoring

Disaster management in dam infrastructure is a critical aspect in preventing catastrophic failures caused by rising water levels. Traditional wireless communication systems, such as Wi-Fi, RF, and GSM, face limitations due to signal interference, power constraints, and network congestion during extreme weather conditions. This study proposes a LiFi-based dam water monitoring system as a faster, more secure, and interference-free communication alternative. The prototype system consists of ultrasonic sensors to measure water levels at different thresholds (low, medium, high), a LiFi transmitter (laser diode) to send data to a remote control station, and a LiFi receiver to decode and process the signals. An ESP32 microcontroller is used to trigger notifications, display alerts on an LCD screen, and activate an alarm system when critical levels are reached. The system also integrates cloud connectivity to send real-time updates to mobile devices and a web interface for historical data visualization. To validate the feasibility of LiFi in disaster-prone dam environments, simulations and prototype tests are conducted to evaluate signal strength, transmission speed, environmental impact, and system response time. Preliminary results indicate that LiFi provides a reliable, low-latency alternative for real-time dam monitoring, with improved data transmission efficiency compared to traditional wireless methods. This study highlights the potential of LiFi in disaster management and proposes further enhancements such as machine learning-based flood prediction models, multisource LiFi redundancy, and extended range communication for large-scale deployments.

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Publication Details

Published
2025-04-23
DOI
https://doi.org/10.1109/raeeucci63961.2025.11048265
Primary Topic
Water Quality Monitoring Technologies
Type
article
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article

LiFi In Disaster Management: A Case Study Of Dam Monitoring

Prem Prakash, M. K. Srilekha, S. Umamaheswari, Pragyan Mishra et al.
Water Quality Monitoring Technologies
article

LiFi In Disaster Management: A Case Study Of Dam Monitoring

Prem Prakash, M. K. Srilekha, S. Umamaheswari, Pragyan Mishra, Khadyout Bhardwaj
article en

Abstract

Disaster management in dam infrastructure is a critical aspect in preventing catastrophic failures caused by rising water levels. Traditional wireless communication systems, such as Wi-Fi, RF, and GSM, face limitations due to signal interference, power constraints, and network congestion during extreme weather conditions. This study proposes a LiFi-based dam water monitoring system as a faster, more secure, and interference-free communication alternative. The prototype system consists of ultrasonic sensors to measure water levels at different thresholds (low, medium, high), a LiFi transmitter (laser diode) to send data to a remote control station, and a LiFi receiver to decode and process the signals. An ESP32 microcontroller is used to trigger notifications, display alerts on an LCD screen, and activate an alarm system when critical levels are reached. The system also integrates cloud connectivity to send real-time updates to mobile devices and a web interface for historical data visualization. To validate the feasibility of LiFi in disaster-prone dam environments, simulations and prototype tests are conducted to evaluate signal strength, transmission speed, environmental impact, and system response time. Preliminary results indicate that LiFi provides a reliable, low-latency alternative for real-time dam monitoring, with improved data transmission efficiency compared to traditional wireless methods. This study highlights the potential of LiFi in disaster management and proposes further enhancements such as machine learning-based flood prediction models, multisource LiFi redundancy, and extended range communication for large-scale deployments.

SRM Institute of Science and Technology (IN)
Climate action
Openalex Percentile: Top 85%
Water Quality Monitoring Technologies
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LiFi In Disaster Management: A Case Study Of Dam Monitoring — Prem Prakash, M. K. Srilekha, et al. · (2025) | TGRS Research Map | TGRS