![[Paper] Sustainability, Environment, and Energy (SEE)](../../../../assets/md5images/29c704a00e426c0ce942437c8c70e83b.png)
Testing and Design of a Portable IoT-based Ultrasonic and GPS Flood Level Monitoring System
Document Types
Paper Presentation
Research Theme (for Paper Presentation and Poster Presentation submissions only)
Sustainability, Environment, and Energy (SEE)
School Name
De La Salle University
Track or Strand
Science, Technology, Engineering, and Mathematics (STEM)
Research Advisor (Last Name, First Name, Middle Initial)
De Guia, Leovine, L.
Start Date
25-6-2026 10:30 AM
End Date
25-6-2026 12:00 PM
Zoom Link/ Room Assignment
DLSU Laguna Campus (In-person) - Enrique K. Razon Jr. Hall - EKR 404
Abstract/Executive Summary
The Philippines is a disaster-prone country facing several catastrophic typhoons annually, due to the country’s geography, being located in the typhoon belt and surrounded by oceans, the devastation of flooding is amplified to a large extent. Despite the dangers flooding poses, the Philippines still has gaps in its flood monitoring systems, with these mostly concentrated in regions around Metro Manila; less developed regions have fewer opportunities to mitigate flooding damage. This study aims to create a small-scale ESP8266-based flood monitoring system by designing a prototype capable of measuring flood depth and geolocation data, and an Adafruit IO dashboard that receives this data and displays it in real-time on a 2D map, serving as an alternative to large-scale flood monitoring systems. It also aims to evaluate the prototype's performance in terms of accuracy under simulated laboratory conditions. The prototype was tested indoors in a hydraulic flume at water depths of 10mm, 20mm, 30mm, 40mm, and 50mm to simulate flooding, and outdoors to ensure it transmitted GPS data accurately to the dashboard. The prototype achieved 97.78% accuracy with a 2.22% percentage error after 15 trials of measuring water depths, well above the acceptable threshold for non-error data display. GPS data were also displayed accurately on the Adafruit IO dashboard. Future prospects include using aggregated data from multiple prototypes to improve flood maps and modifying the prototypes to include flood velocity measurements for flash flood alerts.
Keywords
flood depth; flood monitoring syste; Internet of Things, ultrasonic sensor; Global Positioning System
Initial Consent for Publication
yes
Statement of Originality
yes
Testing and Design of a Portable IoT-based Ultrasonic and GPS Flood Level Monitoring System
The Philippines is a disaster-prone country facing several catastrophic typhoons annually, due to the country’s geography, being located in the typhoon belt and surrounded by oceans, the devastation of flooding is amplified to a large extent. Despite the dangers flooding poses, the Philippines still has gaps in its flood monitoring systems, with these mostly concentrated in regions around Metro Manila; less developed regions have fewer opportunities to mitigate flooding damage. This study aims to create a small-scale ESP8266-based flood monitoring system by designing a prototype capable of measuring flood depth and geolocation data, and an Adafruit IO dashboard that receives this data and displays it in real-time on a 2D map, serving as an alternative to large-scale flood monitoring systems. It also aims to evaluate the prototype's performance in terms of accuracy under simulated laboratory conditions. The prototype was tested indoors in a hydraulic flume at water depths of 10mm, 20mm, 30mm, 40mm, and 50mm to simulate flooding, and outdoors to ensure it transmitted GPS data accurately to the dashboard. The prototype achieved 97.78% accuracy with a 2.22% percentage error after 15 trials of measuring water depths, well above the acceptable threshold for non-error data display. GPS data were also displayed accurately on the Adafruit IO dashboard. Future prospects include using aggregated data from multiple prototypes to improve flood maps and modifying the prototypes to include flood velocity measurements for flash flood alerts.
https://animorepository.dlsu.edu.ph/conf_shsrescon/2026/BoA_SEE/19
