Adaptive Fuzzy Logic-Based LED Power Control for Phaseolus vulgaris Cultivation Using Integrated Image Analysis and Illuminance Sensing

This paper presents the design, implementation, and evaluation of a fuzzy logic-based adaptive lighting strategy for Phaseolus vulgaris cultivation. The objective of this study was to integrate an image-derived plant growth indicator obtained through projected leaf-area estimation into an adaptive pulse-width modulation framework. The proposed system used two input variables: the error between the desired and measured Photosynthetic Photon Flux Density (PPFD) and the estimated projected leaf area. PPFD was indirectly estimated from illuminance measurements acquired using a BH1750 sensor (ROHM Semiconductor, Kyoto, Japan) Mostrar más líneas connected to an Arduino Uno microcontroller, while projected leaf area was obtained from RGB images captured with an Intel RealSense D435 camera and processed in MATLAB R2021a. The fuzzy inference system was implemented using the Mamdani approach and the Fuzzy Logic Designer application. The experimental results showed that the system regulated the PWM signal within a range of 17.00% to 87.85%, corresponding to a power range of 13.65 W to 34.58 W. The projected leaf-area indicator increased from 284.94 cm2 to 392.57 cm2 during the 21-day evaluation period, representing a relative increase of 37.77%. These findings provide preliminary evidence supporting the integration of image-derived projected leaf-area information, illuminance sensing, and fuzzy logic for adaptive lighting regulation in controlled-environment cultivation systems.