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01.09.2014 | Ausgabe 3/2014

Cluster Computing 3/2014

Design and implementation of an integrated management system in a plant factory to save energy

Zeitschrift:
Cluster Computing > Ausgabe 3/2014
Autoren:
Sook-Youn Kwon, Seuc-Ho Ryu, Jae-Hyun Lim

Abstract

Recently, various studies have been conducted to stabilize food production and improve product quality and energy saving efficiency in the face of climate change by integrating ICT (Information and Communication Technology) into existing agricultural technologies. A representative example of this technology, the fully artificial plant factory, facilitates a high degree of environment control and growth prediction based on the cultivation environment and monitoring of crop growth, and has the advantage that environment-friendly crops are cultured. However, the concept has met difficulties in entering the market due to the large investment in facilities and expensive operation costs involved. There are many considerations, including calculating the optimal environment parameters for plants, designing and controlling artificial lights characterized by high-level efficiency and low power consumption, and selecting value-added crops. Among others parameters, those of the optimal environment may be utilized as a very important input element for maximizing plant growth and minimizing energy injection costs. To this end, data, including those related to environment, growth, and energy, will be monitored in real time, and integration management systems will be developed in advance to realize the effective control of connected devices based on the concept of the fully artificial plant factory. However, existing systems are designed for horticultural facilities and have been operated by simply monitoring environment or growth information or individually controlling each device through different interface environments, without considering the energy consumption of the devices. The purpose of this study is to design a method for monitoring in real time integrated environment and growth data and the energy consumption of the devices in a fully artificial plant factory, and to design and implement a plant factory integration management system that actively controls devices based on these data. In the future, the environment/growth/energy data collected from sensors in the proposed system will allow the optimal environment parameters to be calculated for each crop through correlation analysis and each device to be integrated and controlled, contributing to an increase in crop productivity and quality, as well as overall energy consumption efficiency in the plant factory. In addition, the database information collected from the system and then processed will be useful as input data for the integrated database of the SSN (Social Sensor Network) or the intelligent plant factory system.

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