Floodsense North Caloocan: An IoT-Based Community Flood Monitoring and Reporting System

Authors

Ang, Miguel Romero

Bachelor of Science in Computer Science, St. Clare College of Caloocan (Philippines)

Buenviaje, Janessa Marie

Bachelor of Science in Computer Science, St. Clare College of Caloocan (Philippines)

Jacob, Glenn Mark

Bachelor of Science in Computer Science, St. Clare College of Caloocan (Philippines)

Kinkito, Christian Nicole

Bachelor of Science in Computer Science, St. Clare College of Caloocan (Philippines)

Magtoto, Jamaica

Bachelor of Science in Computer Science, St. Clare College of Caloocan (Philippines)

Montaril, Bhon Andrei

Bachelor of Science in Computer Science, St. Clare College of Caloocan (Philippines)

Odsinada, John Roi

Bachelor of Science in Computer Science, St. Clare College of Caloocan (Philippines)

Ruizo, Eliza Ann

Bachelor of Science in Computer Science, St. Clare College of Caloocan (Philippines)

Naturales, Jeanethjoy

Bachelor of Science in Computer Science, St. Clare College of Caloocan (Philippines)

Article Information

DOI: 10.51584/IJRIAS.2026.11060147

Subject Category: Computer Science

Volume/Issue: 11/6 | Page No: 1921-1944

Publication Timeline

Submitted: 2026-06-12

Accepted: 2026-06-17

Published: 2026-07-03

Abstract

Flooding remains one of the most recurring natural disasters in the Philippines, causing significant disruptions to communities, infrastructure, and public safety. North Caloocan is among the areas frequently affected by flooding, particularly during periods of heavy rainfall and typhoons. Traditional flood monitoring methods often rely on manual observation and delayed reporting, resulting in slow dissemination of information and reduced effectiveness of emergency response efforts. This study developed FloodSense North Caloocan, an Internet of Things (IoT)-based community flood monitoring and reporting system designed to provide real-time flood information and improve disaster preparedness within the community.
The system utilizes an ESP32 microcontroller and a waterproof ultrasonic sensor to monitor water levels and transmit data to a cloud-based database. A web application developed using the MERN stack (MongoDB, Express.js, React, and Node.js) enables real-time monitoring, community reporting, flood mapping, and notification services. A quantitative research approach was employed to assess community needs and system acceptance.
Results indicate that residents strongly support the implementation of a real-time flood monitoring system and recognize its potential to improve awareness, preparedness, and response during flood events. Prototype-level validation demonstrated consistent water-level estimation using the JSN-SR04T ultrasonic sensor. Functional testing showed web dashboard update times ranging from 1–3 seconds, notification delays ranging from 4–10 seconds with a 100% notification success rate, and reliable data transmission across all validation trials. These findings indicate that the system can provide timely and dependable flood information for community-based disaster preparedness. The findings demonstrate that FloodSense North Caloocan can serve as an effective tool for enhancing community resilience and supporting local disaster risk reduction and management initiatives.

Keywords

Flood Monitoring, Internet of Things, FloodSense, North Caloocan, Disaster Management, Real Time Monitoring, Community Reporting

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References

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