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Abrajano, M., & co-authors. (2024). IoT water quality monitoring in Philippine off-grid communities. arXiv preprint.

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Article

Multi-Sensor Wireless Network for Integrated Aquatic Ecosystem Monitoring in Quirino Province, Philippines

1Graduate School, University of La Salette, Inc., Santiago City, Philippines

2Engineering Department, Quirino State University-Cabarroguis Campus, Quirino, Philippines

3Schools Division Office-Quirino, Department of Education, Quirino, Philippines

4Schools Division Office-Isabela, Department of Education, Isabela, Philippines


American Journal of Environmental Protection. 2026, Vol. 14 No. 1, 16-21
DOI: 10.12691/env-14-1-3
Copyright © 2026 Science and Education Publishing

Cite this paper:
Wilfredo B. Baniqued, Jordan C. Ursua, Zyrel V. Santos, Jaybert M. Cabañero, Crista Souki D. Asuncion, Romiro G. Bautista. Multi-Sensor Wireless Network for Integrated Aquatic Ecosystem Monitoring in Quirino Province, Philippines. American Journal of Environmental Protection. 2026; 14(1):16-21. doi: 10.12691/env-14-1-3.

Correspondence to: Wilfredo  B. Baniqued, Graduate School, University of La Salette, Inc., Santiago City, Philippines. Email: wilfredo.baniqued@qsu.edu.ph

Abstract

This study deployed a multi-sensor wireless network to assess the health of selected freshwater bodies in Quirino Province by integrating chemical (dissolved oxygen, CO₂), physical (temperature, conductivity, pressure), and optical (turbidity, color) water quality parameters. Recognizing the sensitivity of tropical waters to warming, land-use change, and hydrological variability—and the limitations of low-frequency grab sampling in the Philippines—the study aimed to: (1) characterize spatial–temporal patterns in a midstream river, an agricultural stream, and a pond; (2) examine relationships between dissolved oxygen (DO) and key drivers such as temperature and CO₂; (3) identify hypoxia thresholds and risk periods; and (4) evaluate the effectiveness of wireless monitoring. Sensors for optical DO, NDIR CO₂, temperature, conductivity, pressure, turbidity, and color were installed at three sites and operated continuously for six months at 5-minute intervals. Periodic grab samples validated sensor readings. Data were analyzed using descriptive statistics, correlation, regression, and event-based analysis. Mean DO remained above the 5 mg/L guideline but declined from river (~7.3 mg/L) to stream (~6.4 mg/L) to pond (~5.9 mg/L). The pond exhibited the highest temperatures, often exceeding 30 °C, and showed pronounced nighttime DO minima. Temperature was the strongest inverse predictor of DO (r ≈ –0.66 to –0.78), with CO₂, turbidity, and color contributing additional negative effects. Hypoxic events were rare in the river but more frequent in the stream and pond, particularly after storms.Sensor validation showed strong agreement with grab samples, while continuous monitoring captured short-lived DO depressions missed by conventional methods. The study supports institutionalizing wireless monitoring and establishing site-specific early warning thresholds to mitigate oxygen stress under climate and land-use pressures.

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