Real-Time Monitoring and Sonification of Mung Bean (Vigna radiata) Bioelectrical Responses to LED Light Spectra Using an ESP32-Based Embedded System

Eddy Lybrech Talakua; Eko Haris Siswanto; Mahesa Sangga Bhuwana; Erwin Dhansiswara

doi:10.33650/jeecom.v8i3.16861

Real-Time Monitoring and Sonification of Mung Bean (Vigna radiata) Bioelectrical Responses to LED Light Spectra Using an ESP32-Based Embedded System

DOI: https://doi.org/10.33650/jeecom.v8i3.16861

Authors

(1) * Eddy Lybrech Talakua

(Universitas Widya Kartika)
        Indonesia
(2)  Eko Haris Siswanto   (Universitas Widya Kartika)
        Indonesia
(3)  Mahesa Sangga Bhuwana   (Universitas Widya Kartika)
        Indonesia
(4)  Erwin Dhansiswara   (Universitas Widya Kartika)
        Indonesia
(*) Corresponding Author

Abstract

The advancement of indoor farming as a solution to limited agricultural land has driven the use of Light Emitting Diodes (LEDs) as artificial lighting sources capable of controlling plant growth environments. Variations in LED light spectra are known to influence plant physiological activities, including changes in bioelectrical signals that can serve as early indicators of plant physiological conditions. However, most bioelectrical monitoring systems still present information in numerical or graphical formats, which are less intuitive for direct real-time interpretation. This study presents a pilot investigation of the effect of four LED light spectra (red, blue, green, and white) on the bioelectrical responses of a mung bean plant (Vigna radiata), together with the development of an ESP32-based embedded system that performs real-time bioelectrical signal acquisition, timestamped data logging, and Parameter Mapping Sonification of the signals into musical notes. The system integrates bioelectrical electrodes, an AD8232 signal-conditioning module, an ESP32 microcontroller, a DS3231 RTC module, a microSD card, and a DFPlayer Mini audio module. Measurements were repeated across four trials for each LED spectrum on a single test plant. Blue and white LEDs produced the highest mean Vrms (1.431 V), red LED produced the highest average Vpp (0.448 V), and green LED produced the lowest average Vpp (0.311 V); trial-to-trial variability (SD up to 0.18 V for Vpp) indicates that further biological replication is needed before the spectral effect can be generalized. The system successfully performed real-time acquisition, logging, and sonification, converting bioelectrical voltage into 28 distinct musical notes. These preliminary results indicate that the proposed embedded architecture is technically feasible for auditory representation of plant bioelectrical dynamics and may support the future development of non-destructive, smart-agriculture monitoring tools; confirming the generality of the LED-spectrum effect and the perceptual benefit of sonification will require larger biological replication and a formal user study.

Keywords

Plant Bioelectrical Signals, ESP32, AD8232, LED Light Spectrum, Sonification.

Full Text: PDF

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