Issue |
BIO Web Conf.
Volume 167, 2025
5th International Conference on Smart and Innovative Agriculture (ICoSIA 2024)
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Article Number | 05004 | |
Number of page(s) | 8 | |
Section | Smart and Precision Farming | |
DOI | https://doi.org/10.1051/bioconf/202516705004 | |
Published online | 19 March 2025 |
Design of Smart Plant Electrical Signal Monitoring System for Indoor Farming
1 Smart Agriculture Research Center, Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Jln. Flora No.1 Bulaksumur Yogyakarta 55281, Indonesia
2 Department of Agro-Environmental Sciences, Faculty of Agriculture, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 810-0395, Japan
* Corresponding author: lilik-soetiarso@ugm.ac.id
Precision agriculture is widely applied in indoor farming to optimize resource use and improve sustainability. Spectral technology has limitations in operation in plant health monitoring in indoor farming. A concept of plant physiology, plant electrical signals, is able to be developed as a basic principle in plant health monitoring systems. This research investigates the design of a plant monitoring system based on plant electrical signals. The system integrates Ag wire electrodes for acquiring plant electrical signals. Low-pass filters and operational amplifiers are utilized signal processing, while microcontrollers and data loggers handle data storage and analysis. Calibration for this system needs a function generator. The calibration result is analyzed using statistical methods such as MAPE. The system will apply various advanced analysis techniques such as time domain, frequency domain, and machine learning methods. The goal of such analysis is to improve early detection of plant stress contributing to more efficient crop management in indoor farming systems. This monitoring system potentially improves plant health and supports sustainable agricultural practices. By leveraging the rapid response of plant electrical signals to environmental changes, the system is the first step for optimizing plant growth by providing real-time monitoring and environmental recommendations.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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