• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.5
• /
• pp.379-386
• /
• 2021

This study was undertaken to develop a cascade-type continuous culture system (CCCS) that combines both ICT and biotechnology (BT), for the mass production of microalgae. This system is capable of maintaining the essential culture conditions of pH, temperature, carbon dioxide, and illuminance control, which are key parameters for the growth of microalgae, and is economical for producing microalgae regardless of the season or location. It has the added advantage of providing stable and high productivity. In the current study, this system was applied to culture microalgae for 71 days, with subsequent analysis of the experimental data. The initial O.D. of the culture measured from incubator 1 was 0.006. On the 71st day of culture, the O.D.s obtained were 0.399 (incubator 1), 0.961 (incubator 2), 0.795 (incubator 3), and 0.438 (incubator 4), thereby confirming the establishment of continuous culture. Thus, we present a smart-farm based on ISMC (in-situ monitoring and control) for a mass culture method. We believe that this developed technology is suitable for commercialization, and has the potential to be applied to hydroponics-based cultivation of microalgae and cultivation of high-value-added medicinal plants as well as other plants used in functional foods, cosmetics, and medical materials.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.3
• /
• pp.185-199
• /
• 2019

Korea's facility horticulture has developed remarkably in a short period of time. However, in order to secure international competitiveness in response to unfavorable surrounding conditions such as high operating costs and market opening, it is necessary to diagnose the problems of facility horticulture and prepare countermeasures through analysis. The purpose of this study was to analyze the case of leading farmers by introducing information and communication technology (ICT) in hydroponic cultivation agriculture and horticulture, and to examine how agricultural technology utilizing smart farm and big data of facility horticulture contribute to farm productivity. Crop growth information gathering and analysis solutions were developed to analyze the productivity change factors calculated from hydroponics tomato farms and strawberry farms. The results of this study are as follows. The application range of the leaf temperature was verified to be variously utilized such as house ventilation in the facility, opening and closing of the insulation curtain, and determination of the initial watering point and the ending time point. Second, it is necessary to utilize water content information of crop growth. It was confirmed that the crop growth rate information can confirm whether the present state of crops is nutrition or reproduction, and can control the water content artificially according to photosynthesis ability. Third, utilize EC and pH information of crops. Depending on the crop, EC values should be different according to climatic conditions. It was confirmed that the current state of the crops can be confirmed by comparing EC and pH, which are measured from the supplied EC, pH and draining. Based on the results of this study, it can be confirmed that the productivity of smart farm can be affected by how to use the information of measurement growth.

• Korean Journal of Construction Engineering and Management
• /
• v.23 no.1
• /
• pp.98-105
• /
• 2022

It is essential for vertical smart farms that artificially grow crops in an enclosed space to properly utilize air environment facilities to create an appropriate growth environment. However, domestic vertical smart farm companies are creating a growing environment by relying on empirical data rather than systematic methods. Using IoT to create a growing environment based on systematic and precise monitoring can increase crop production yield and maximize profitability. This study aims to construct a monitoring system using IoT and to analyze the cause by demonstrating the imbalance of temperature environment, which is a significant factor in crop cultivation. 1) The horizontal temperature distribution of the multi-layer shelf was measured with different operating methods of LED and air conditioner. As a result, there was a temperature difference of "up to 1.7℃" between the sensors. 2) As a result of measuring the vertical temperature distribution, the temperature difference was "up to 6.3℃". In order to reduce this temperature gap, a strategy for proper arrangement and operation of air conditioning equipment is required.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.12 no.3
• /
• pp.465-470
• /
• 2017

This paper designs and implements a smart garden system using probabilistic filter algorithm using SLAM that can be used in apartment or veranda. To do this, we used Arduino and environtal sensors, which are open hardware controllers, and designed to control and observe automatic water supply, lighting, and growth monitoring with three wireless systems (Bluetooth, Ethernet, WiFi). This system has been developed to make it possible to use it in an indoor space such as an apartment, rather than a large-scale cultivation system such as a conventional plant factory which has already been widely used. The developed system collects environmental data by using soil sensor, illuminance sensor, humidity sensor and temperature sensor as well as control through smartphone app, analyzes the collected data, and controls water pump, LED lamp, air ventilation fan and so on. As a wireless remote control method, we implemented Bluetooth, Ethernet and WiFi. Finally, it is designed for users to enable remote control and monitoring when the user is not in the house.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.135-135
• /
• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• Smart Media Journal
• /
• v.7 no.3
• /
• pp.51-56
• /
• 2018

Banana is the eighth most important crop in the world designated by the United Nations Food and Agriculture Organization (FAO). In terms of production, it is the fourth most harvested crop following wheat, rice, and corn, considered to be a promising food source for mankind as it is not only scrumptious but also rich in nutrients. However, abnormal cultivation methods that mankind has invented to breed bananas is currently pushing them to the state of extinction. The aim of this study is to develop information-rich digital contents that can easily and intriguingly convey information about steadily but certainly increasing risk of banana extinction. The end-users are middle and high school students who are assumed to be aware of the agricultural revolution through their school curriculum. The linear storytelling method was meant to encourage the end-users to be interested in the causes and processes in which banana has become endangered. For generating a natural interaction between the content and the end-users, a parallel, upper-lower structure was used, in which the relationship between the stories comprising several stages and the information graphic supporting each story is represented. This paper can support an information campaign about the endangered species.

• Journal of Digital Convergence
• /
• v.19 no.12
• /
• pp.331-337
• /
• 2021

The adaptation of smartfarm technology that converges ICT is increasing productivity and competitiveness in the agriculture. Technologies have been developed that enable environmental monitoring through various sensors and automatic control of the cultivation environment, and researches are underway to advance smartfarm technology using data generated from smartfarms. In this paper, an environmental control method to reduce the energy consumption of a smartfarm by using the environment and control data of the smartfarm is proposed. It was confirmed that energy consumption could be reduced compared to an independent environmental control method by creating an environmental prediction model using accumulated environmental data and selecting a control method to minimize energy consumption in a given situation by considering multiple environmental factors. In the future, research is needed to obtain higher energy efficiency through the advancement of the predictive model and the improvement of the complex control algorithms.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.20 no.5
• /
• pp.111-120
• /
• 2021

A tractor is an agricultural machine that performs farm work, such as cultivation, soil preparation, loading, bailing, and transporting, through attached working implements. Farm work must be carried out on time per the growing season of crops. As a result, the reliability of a tractor's transmission is vital. Ideally, the transmission's design should reflect the actual load during agricultural work; however, configuring such a measurement system is time- and cost-intensive. The design and analysis of a transmission are, therefore, mainly performed by empirical methods. In this study, a tractor with a measurement system was used to measure the actual working load in the field. Its hydro-mechanical transmission was then analyzed using the measured load. It was found that the velocity factor, load distribution factor, lubrication factor, roughness factor, relative notch sensitivity factor, and life factor affect the gear strength of the transmission. Also, loading conditions have a significant influence on the reliability of the transmission. It is believed that transmission reliability can be enhanced by analyzing the actual load on the transmission, as performed in this study.

• Journal of Mushroom
• /
• v.15 no.4
• /
• pp.264-268
• /
• 2017

In the 21st century, information and communication technology (ICT) worldwide presents a new vision for agriculture. Time and place, as well as the high-tech industry, to overcome barriers to the fusion of the so-called "smart agriculture," are changing the agricultural landscape. Core container production in precision agriculture for mushroom cultivation, optimal temperature, humidity, irradiation, self-regulation of factors such as carbon dioxide, and environment for mushroom cultivation were adopted. Lentinula edodes (shiitake) is an edible mushroom native to East Asia, cultivated and consumed in many Asian countries. It is considered to be medicinal in certain practices of traditional medicine. We used different controlled light sources (Blue-Red-White-combined LED, blue LED, red LED, and fluorescent light) with different LED radiation intensities (1.5, 10.5, and $20.5{\mu}mol/m^2s$ for LEDs) to compare growth and development. Mushrooms were treated with light in a 12-hour-on/12-hour-off cycle, and maintained in a controlled room at $19{\sim}21^{\circ}C$, with 80~90% humidity, and an atmospheric $CO_2$ concentration of 1,000 ppm for 30 days. Growth and development differed with the LED source color and LED radiation intensity. Growth and development were the highest at $10.5{\mu}mol/m^2s$ of blue LED light. After harvesting the fruit bodies, we measured their weight and length, thickness of pileus and stipe, chromaticity, and hardness. The $10.5{\mu}mol/m^2s$ blue-LED-irradiated group showed the best harvest results with an average individual weight of 39.82 g and length of 64.03 mm, pileus thickness of 30.85 mm and pileus length of 43.22 mm, and stipe thickness of 16.96 mm with fine chromaticity and hardness. These results showed that blue LED light at $10.5{\mu}mol/m^2s$ s exerted the best effect on the growth and development of L. edodes (shiitake) mushroom in the ICT-system container-type environment.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.1
• /
• pp.131-137
• /
• 2021

This study estimated acreage response functions for greenhouse paprika, greenhouse strawberry, open-land garlic, and open-land spinach by using Gyeongsangnamdo agricultural income data. The results show that the cultivation area for greenhouse paprika increased because the agricultural management costs decreased, and the risk of price volatility was relatively low. On the other hand, the cultivation area for greenhouse strawberries decreased due to increasing agricultural management costs and the greater risk of price volatility. In the case of open-land garlic and spinach, the cultivation area remained stagnant due to the greater risk of price volatility, despite increasing agricultural revenue. We derived several policy implications from our results. The risk of price volatility in agricultural products is greater for crops grown on land rather than crops grown in greenhouses. Therefore, the local government needs to adopt the "agricultural revenue guarantee insurance" in preference to crops grown on land rather than crops grown in greenhouses. On the other hand, in the case of greenhouse crops, agricultural management costs are very high. Thus, local government should focus on replacing old facilities and supplying smart-farm facilities that reduce agricultural management costs such as heating costs.