Nutrient Solution Management System for Smart Farms and Plant Factory

Abstract

We present an automated system for nutrient solution management. Prior arts usually measure only pH and EC of the nutrient solutions for maintenance. When EC drops, they just simply add concentrated nutrient to the horticulture bed. Such approach can maintain the density of nutrient solution but cannot maintain the rates of individual ion particles. To prevent nutrition related disorders, fertilization methods with ion selective electrodes are widely introduced. This trend measures individual ion concentration of nutrient solution to maintain appropriate nutrient composition by supplying only insufficient ions. Many researchers have suggested ISE based automated fertilization systems. However, they failed to control a chemical artifact called ion interference effect, which becomes greater at higher density. Our system measures individual concentration of multiple ions and add only deficient nutrients, while handling the ion interference effect issue. To ensure the performance of ion selective electrodes, the system also performs fully automated 3-point calibration 24 times a day. A machine learning algorithm is applied on the sensory parts to remove ion interference effect which make measurement of complex solution with ISE almost impossible. With automated calibration and signal processing technology, the system robustly and continuously maintains nutrient condition for plants. We suggest applying this system on closed hydroponic systems such as smart farms or plant factory, to reduce water consumption and to provide more appropriate environment for the crops.

Examination of the Global Plant Factory's National Competitiveness via Artificial Intelligence-Driven Research Analysis

“…Leveraging advanced computer systems, these facilities meticulously manage crucial environmental parameters, including temperature, humidity, light exposure, CO2 concentration, and nutrient composition. This orchestration of conditions aims to attain an unparalleled level of precision, fostering an agricultural paradigm wherein crops are produced continuously and in harmony with human-defined parameters [1][2][3]. The plant factory concept can be perceived as an advanced evolution within the continuum of facility-based farming practices [4][5][6].…”

A Systematic Review of Current Trends in Artificial Intelligence for Smart Farming to Enhance Crop Yield

“…In intelligent surveys, each planted area had various criteria and could be measured from both quantity and quality. Some critical Criteria for Smart Farming, such as nutrients [12], soil [13], pests [14], irrigation [15] etc., determine the ability and suitability of certain types of crops. In most situations, different criteria usually exist in one crop field, let alone for the same crop growing on all available land for agriculture; because it requires a specific analysis of the location needed to map the production of plant products effectively and efficiently [16].…”

Crop Growth Monitoring System in Vertical Farms Based on Region-of-Interest Prediction

“…To ensure crop yields in the vertical farm system, it is also important to maintain an environment conducive to crop growth via the continuous monitoring of farm conditions. Most current farm monitoring systems [3] are designed to maintain an environment that is consistent with the established practices for growing crops, and such methods are based on knowledge about cultivation for growing crops rather than their status. However, crop states are critical for determining the optimal cultivation environment, and by continuously monitoring crop statuses, a proper crop-optimized farm environment can feasibly be maintained.…”