IoT-Based water quality monitoring and sustainable modeling for smart campuses

Kurniawan, Fachrul ORCID: https://orcid.org/0000-0002-3709-8764, Azizah, Miladina Rizka, Hasanah, Novrindah Alvi and Wibawa, Aji Prasetya (2026) IoT-Based water quality monitoring and sustainable modeling for smart campuses. IoT-Based Water Quality Monitoring and Sustainable Modeling for Smart Campuses, 10 (2). pp. 398-406. ISSN 2580-0760

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Abstract

This study proposes an IoT-based water quality monitoring framework integrated with a continuous sustainable modeling approach for smart campus applications. A total of 404 sensor observations were collected, including pH, turbidity, temperature, and Total Dissolved Solids (TDS). A continuous water suitability score ranging from 0 to 1 was constructed based on WHO drinking water standards, and Multiple Linear Regression was employed to model the relationship between water quality parameters and the suitability score. The main contribution of this study lies in the development of a lightweight analytical framework that combines continuous regression modeling with threshold-based classification to support real-time decision-making in resource-constrained environments. The dataset was divided into 90% training and 10% testing data. The results show that the proposed framework achieved a classification accuracy of 88.5% based on threshold mapping of regression outputs, with a misclassification rate of 11.5%. These findings demonstrate the effectiveness of integrating IoT-based monitoring with interpretable and computationally efficient analytical models for sustainable campus water management.

Item Type:	Journal Article
Keywords:	iot-based monitoring; monitoring water; smart green campus; visualization
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems 08 INFORMATION AND COMPUTING SCIENCES > 0806 Information Systems > 080699 Information Systems not elsewhere classified 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing 08 INFORMATION AND COMPUTING SCIENCES > 0806 Information Systems
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Fachrul Kurniawan
Date Deposited:	17 Jun 2026 15:04

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