Design of a Nutrient and Environment Monitoring IoT Device in Vertical Hydroponic System

This study presents the design and performance evaluation of an Internet of Things (IoT)-based nutrient and environmental monitoring device for vertical hydroponic farming. The system employs multiple sensors to measure pH, Total Dissolved Solids (TDS), nutrient temperature, air temperature, and air humidity. Data are transmitted via ESP32 and integrated with the Arduino IoT Cloud, enabling real-time monitoring through a web dashboard and IoT Remote mobile application. A 10-day testing period was conducted to compare sensor outputs against standard calibrator references. The device demonstrated minimal bias (e.g., 0.20 for pH, 0.51"¯°C for nutrient temperature) and high precision (100.00%) across all parameters. Accuracy ranged from 92.33% (TDS) to 98.24% (nutrient temperature), while error rates were relatively low (e.g., 1.76% for nutrient temperature and 7.67% for TDS). These findings validate the system's reliability and consistency, supporting its potential for scalable implementation in precision-controlled, real-time monitoring applications within urban agriculture.

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Publication Details

Journal
Ultima Computing Jurnal Sistem Komputer
Published
2025-06-30
DOI
https://doi.org/10.31937/sk.v17i1.4145
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Design of a Nutrient and Environment Monitoring IoT Device in Vertical Hydroponic System

Fahmy Rinanda Saputri, Ricardo Linelson
Ultima Computing Jurnal Sistem Komputer
Water Quality Monitoring Technologies
article

Design of a Nutrient and Environment Monitoring IoT Device in Vertical Hydroponic System

Fahmy Rinanda Saputri, Ricardo Linelson
article en

Abstract

This study presents the design and performance evaluation of an Internet of Things (IoT)-based nutrient and environmental monitoring device for vertical hydroponic farming. The system employs multiple sensors to measure pH, Total Dissolved Solids (TDS), nutrient temperature, air temperature, and air humidity. Data are transmitted via ESP32 and integrated with the Arduino IoT Cloud, enabling real-time monitoring through a web dashboard and IoT Remote mobile application. A 10-day testing period was conducted to compare sensor outputs against standard calibrator references. The device demonstrated minimal bias (e.g., 0.20 for pH, 0.51"¯°C for nutrient temperature) and high precision (100.00%) across all parameters. Accuracy ranged from 92.33% (TDS) to 98.24% (nutrient temperature), while error rates were relatively low (e.g., 1.76% for nutrient temperature and 7.67% for TDS). These findings validate the system's reliability and consistency, supporting its potential for scalable implementation in precision-controlled, real-time monitoring applications within urban agriculture.

Ultima Computing Jurnal Sistem KomputerVol. 17(1)
Universitas Multimedia Nusantara
Openalex Percentile: Top 81%
Water Quality Monitoring Technologies
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