Development of a smart hydroponic vertical farm for diversified crop cultivation

• Main Author: Alajas, Oliver John Y.
• Format: text
• Language: English
• Published: Animo Repository 2023
• Subjects: Vertical gardening; Crop diversification; Hydroponics; Computational intelligence; Electrical and Electronics
• Online Access: https://animorepository.dlsu.edu.ph/etdm_ece/26; https://animorepository.dlsu.edu.ph/context/etdm_ece/article/1030/viewcontent/DEVELOPMENT2_OF_A_SMART_HYDROPHONIC_VERTICAL_FARM_FOR_DIVERSIFIED.pdf
• Institution: De La Salle University

Hydroponics is a type of cultivation process that involves the use of nutrient-rich water as a source of micro and macro-nutrients for crops to thrive and grow. It is an innovation from the traditional farming method that involves using soil on farmlands. Hydroponics is typically employed in a controlled environment where the temperature of the environment and, the pH level and electrical conductivity level of the nutrient-rich solution is being maintained. However, one striking limitation that can be seen in this type of horticultural practice is the lack of flexibility in terms of creating an environment where polyculture can be applied. Polyculture is a type of horticultural practice that involves using two or more crops to be grown in a single land space during a predetermined growing period. This research explores the feasibility of applying row-intercropping polyculture through an indoor hydroponic vertical farm by growing three crops (lettuce, basil, and arugula) simultaneously in a pre-planned cultivation cycle with computational-intelligence-optimized growth parameters (pH level and electrical conductivity), vision-based crop nutrient and weight assessment, and a browser-based temperature, light intensity, and video surveillance monitoring via open-sourced home automation platform. Furthermore, all these crops were cultivated in a custom-designed indoor hydroponic vertical farm prototype that has automated features to minimize human intervention. Also, suitable algorithms were used to design the prediction and optimization models in the study. Optimization results for the pH and EC levels were implemented in the cultivation cycle, and correlational analysis was performed. Techno-economic analysis was used to determine the profitability of the prototype which can be used as a reference for future design improvements and mass production. Overall, this research’s main goal is to popularize the use of automated technologies in indoor cultivation and improve traditional farming practices through tech-based innovation.