Development and implementation of an adaptive LED lighting system for controlled environment agriculture

• Main Author: Santiago, Robert Martin C.
• Format: text
• Language: English
• Published: Animo Repository 2020
• Subjects: LED lighting; Electronics in agriculture; Tomatoes —Climatic factors; Electrical and Computer Engineering; Systems and Communications
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/6313; https://animorepository.dlsu.edu.ph/context/etd_masteral/article/13361/viewcontent/Santiago_RobertMartin_11573481_NEW_Redacted.pdf
• Institution: De La Salle University

The idea of creating a microclimate condition for plant cultivation which involves controlling critical factors such as light, temperature, water, and nutrition for their satisfactory growth has been the focus of various researches for the past recent years. However, the implementations done on previous studies were either limited to understanding the growth response of plants to different light characteristics or applications that have supervised controls or using complex and expensive sensors which prevent these systems to be deployed on larger agricultural sector. An improvement to these previous studies is the development and implementation of a lighting system that utilizes solid-state lighting based on the use of light-emitting diodes (LEDs) integrated with an intelligent algorithm to be adaptive to the light requirements of specific plants. In this study, tomato plants are cultivated inside a growth chamber and light characteristics that are delivered to the tomato plants are controlled by the adaptive LED lighting system. Initially, a lighting profile is created which is based on previous studies about the response of tomato plants to different light characteristics. This includes the light quality or spectral distribution of light, light quantity or irradiance levels, and light duration or photoperiod for every growth stage that significantly improve over-all plant development. The lighting profile is the basis of the system in selecting appropriate conditions of light for the plants. This selection is done by a fuzzy logic system as well as the control to the activation and deactivation of the lighting system as needed by the tomato plants. The input ambient light condition to the fuzzy logic system results to the output light characteristics delivered to the plants. The results show that the study is able to develop and implement an adaptive LED lighting system for controlled environment agriculture that delivers necessary light quality, light quantity, and light duration based on the determined lighting profile for tomato plants. Moreover, applications of this study are expected to lead to improvements in plant characteristics, energy consumption, and over-all productivity.