Aloran Water Level Monitoring System with Web Data Logging Utilizing Ultrasonic Sensor

The Aloran Water Level Monitoring System was developed to enhance disaster preparedness by integrating real-time monitoring, data logging, and warning mechanisms. Utilizing ultrasonic sensors, Arduino UNO R3, and ESP8266 microcontrollers, the system measured water levels and transmitted data to a local web server. A GSM module sent real-time alerts, while warning lights activated at critical thresholds. Testing confirmed high accuracy in water level measurement, effective real-time data logging, and timely notifications, earning a 4.42 general weighted mean (“Very Good”). The system proved reliable and cost-effective for flood monitoring and disaster risk reduction. Recommendations include incorporating solar-powered modules for remote deployment, cloud-based servers for broader accessibility, and predictive analytics for improved flood forecasting.

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Publication Details

Journal
MDP Student Conference
Published
2025-04-22
DOI
https://doi.org/10.35957/mdp-sc.v4i1.11241
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
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article

Aloran Water Level Monitoring System with Web Data Logging Utilizing Ultrasonic Sensor

W Amin, Gail Diane Salaguste, Charlyn M Gabayan, Allene S. Pereno et al.
MDP Student Conference
Water Quality Monitoring Technologies
article

Aloran Water Level Monitoring System with Web Data Logging Utilizing Ultrasonic Sensor

W Amin, Gail Diane Salaguste, Charlyn M Gabayan, Allene S. Pereno, Jelly Grace A. Caw-it
article en

Abstract

The Aloran Water Level Monitoring System was developed to enhance disaster preparedness by integrating real-time monitoring, data logging, and warning mechanisms. Utilizing ultrasonic sensors, Arduino UNO R3, and ESP8266 microcontrollers, the system measured water levels and transmitted data to a local web server. A GSM module sent real-time alerts, while warning lights activated at critical thresholds. Testing confirmed high accuracy in water level measurement, effective real-time data logging, and timely notifications, earning a 4.42 general weighted mean (“Very Good”). The system proved reliable and cost-effective for flood monitoring and disaster risk reduction. Recommendations include incorporating solar-powered modules for remote deployment, cloud-based servers for broader accessibility, and predictive analytics for improved flood forecasting.

MDP Student ConferenceVol. 4(1)
Southern University of Science and Technology (CN), University of Pangasinan (PH)
Openalex Percentile: Top 89%
Water Quality Monitoring Technologies
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