IoT-based real-time monitoring of agricultural wastewater using Raspberry Pi, Node-RED, and Grafana

Abdul Latiff, Anas and Mohd Faizu, Nur’in Batrisyia and Roslizar, Ahmad Muzammil and Zaini, Muhammad Aizat Zaim and Idris, Fakrulradzi and Berahim, Zulkarami (2025) IoT-based real-time monitoring of agricultural wastewater using Raspberry Pi, Node-RED, and Grafana. Bulletin of Electrical Engineering and Informatics, 14 (6). pp. 4665-4677. ISSN 2089-3191

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Abstract

This study introduces an internet of things-based agricultural wastewater monitoring system (IoT-AWMS) designed to enhance water management through real-time monitoring and advanced sensor integration. The system employs a Raspberry Pi for centralized control, node-RED for automation, InfluxDB for data storage, and Grafana for visualization. A key innovation is the integration of an alternative sensing approach for estimating electrical conductivity (EC), complementing conventional sensors for total dissolved solids (TDS), water temperature (DS18B20), and ambient conditions (DHT11). The system achieves over 85% accuracy in estimating EC across diverse water samples, including drinking water, agricultural runoff, and fertilizer-enriched solutions. Compared with conventional approaches, IoT AWMS demonstrates superior accuracy, scalability, and cost-effectiveness. Its modular design supports applications in nutrient runoff detection, contamination monitoring, and optimized water resource utilization, with broader potential in precision farming and environmental monitoring. This work contributes a robust, adaptable IoT framework for sustainable agricultural water management.

Item Type:	Article
Uncontrolled Keywords:	Agricultural, Fertilizer sensor, Internet of Things, Modern agriculture, Raspberry Pi, Water sensor
Divisions:	Faculty Of Electronics And Computer Technology And Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	03 Feb 2026 00:27
Last Modified:	03 Feb 2026 00:27
URI:	http://eprints.utem.edu.my/id/eprint/29401
Statistic Details:	View Download Statistic

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