• Korean journal of applied entomology
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• v.59 no.1
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• pp.55-64
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• 2020

Smart greenhouses are primarily used for growing fruits and vegetables, such as sweet peppers, tomatoes, strawberries. Although the number of smart greenhouses has been increasing exponentially, no studies have been performed to evaluate the state of smart greenhouses in Korea. Therefore, this study was conducted to determine current state of smart greenhouses with regard to greenhouse specifications, crop growing methods, pests, and user satisfaction in Korea. Contact information for smart greenhouses was provided by the officials of local agricultural research and extension services. This survey was conducted by visiting each greenhouse. Results showed that approximately 50% of surveyed smart greenhouses were between 3,300 ㎡ and 6,600 ㎡. The most frequently chosen method for pest control was chemical pesticides (97.1%). Powdery mildew and gray mold comprised 54.4% and 33.8% of the crop diseases, respectively. All tomato greenhouse farmers considered whiteflies the most problematic pest. In contrast, 76.5% and 70.6% of sweet pepper farmers believed thrips and aphids posed significant threats, respectively. The mean satisfaction score was 7.5 out of 10 points, with 10 being "extremely satisfied". These results will aid in decision making with respect to the management of current smart greenhouses and the design of future smart farms in Korea.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.37-45
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• 2023

In line with the 4th Industrial Revolution, facility maintenance technologies for building smart factories are receiving attention and are being advanced. In addition, technology is being applied to smart farms and smart fisheries following smart factories. Among them, in the case of a recirculating aquaculture system, there is a motor pump that circulates water for a stable quality environment in the tank. Motor pump maintenance activities for recirculating aquaculture system are carried out based on preventive maintenance and data obtained from vibration sensor. Preventive maintenance cannot cope with abnormalities that occur before prior planning, and vibration sensors are affected by the external environment. This paper proposes an anomaly detection algorithm that utilizes ADTK, a Python open source, for motor pump anomaly detection based on data collected through current sensors that are less affected by the external environment than noise, temperature and vibration sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.376-378
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• 2021

According to the 2020 Global Climate Report released by the World Meteorological Organization, the average temperature of the Earth in 2019 was measured 1.1℃ higher on average than the temperature measured between 1850 and 1900 before industrialization. The change in average temperature affects the distribution of plants, and according to the vulnerability analysis paper, it can be seen that there is a change in the distribution area of plants when the average temperature rises. In this paper, to cope with these environmental changes, we propose a method of fabricating intermittent flow hydroponic smart farms using Arduino and sensors and controlling them through PCs and applications. The manufactured hydroponic smart farm identifies the farm's temperature and humidity, positive pH concentration, illumination, and water quality to check the amount of pumping, supplement LED control, sensor condition, overall management and cultivation of the farm, and grows in an appropriate environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.344-345
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• 2022

ogy is being used in many fields, such as smart farms, smart oceans, smart homes, and smart energy. Various IoT terminals are used for these IoT services. Here, IoT devices are physically installed in various places. A malicious attacker can access the IoT service using an unauthorized IoT device, access unauthorized important information, and then modify it. In this study, to solve these problems, we propose an authentication system for IoT devices used in IoT services. The IoT device authentication system proposed in this study consists of an authentication module mounted on the IoT device and an authentication module of the IoT server. If the IoT device authentication system proposed in this study is used, only authorized IoT devices can access the service and access of unauthorized IoT devices can be denied. Since this study proposes only the basic IoT device authentication mechanism, additional research on additional IoT device authentication functions according to the security strength is required.IoT technol

• Journal of Sensor Science and Technology
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• v.33 no.4
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• pp.230-236
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• 2024

This study aimed to analyze the environmental factors affecting tomato growth by examining the correlation between weather and growth environment sensor data from P Smart Farm located in Gwangseok-myeon, Nonsan-si, Chungcheongnam-do. Key environmental variables such as the temperature, humidity, sunlight hours, solar radiation, and daily light integral (DLI) significantly affect tomato growth. The optimal temperature and DLI conditions play crucial roles in enhancing tomato growth and the photosynthetic efficiency. In this study, we developed a model to correct and predict the time-series variations in internal environmental sensor data using external weather sensor data. A linear regression analysis model was employed to estimate the external temperature variations and internal DLI values of P Smart Farm. Then, regression equations were derived based on these data. The analysis verified that the estimated variations in external temperature and internal DLI are explained effectively by the regression models. In this research, we analyzed and monitored smart-farm growth environment data based on weather sensor data. Thereby, we obtained an optimized model for the temperature and light conditions crucial for tomato growth. Additionally, the study emphasizes the importance of sensor-based data analysis in dynamically adjusting the tomato growth environment according to the variations in weather and growth conditions. The observations of this study indicate that analytical solutions using public weather data can provide data-driven operational experiences and productivity improvements for small- and medium-sized facility farms that cannot afford expensive sensors.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.764-771
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• 2018

Domestic and foreign agricultural environments nowadays are undergoing various changes such as aging of agricultural population, increase of earned population, rapid climate change, diversification of agricultural product distribution structure, depletion of water resources and limited cultivation area. In order to respond to various environmental changes in recent agriculture, practical use of Smart Greenhouse to easily record, store and manage crop production information such as crop growing information, growth environment and agriculture work log, Interest is growing. In this paper, we propose a system that collects the situation information necessary for growth such as temperature, humidity, solar radiation, CO2 concentration, and monitor the collected data, which can be measured in the rhizosphere of the crop. We have developed a system that collects data such as temperature, humidity, radiation, and growth environment data, which are measured by data obtained from the rhizosphere measuring section of a growing crop and measured by a sensor, and transmitted to a wireless communication gateway of 400 MHz. We developed the integrated SW that can monitor the rhythm environment data and visualize the data by using cloud based data. We can monitor by graph format and data format for visualization of data. The existing smart farm managed crops and facilities using only the data within the farm, and this study suggested the most efficient growth environment by collecting and analyzing the weather and growth environment of the farms nationwide.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.43-52
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• 2018

Livestock production is the second largest economic activity of Pakistan's rural population, more specifically; sixty-seven percent of Pakistan's total population that live in rural areas sources their income from livestock activities. As this subsector of agriculture within rural Pakistan is so critical to Pakistan's economy it is especially important to further develop the sector through the introduction of cost effective, efficient, and practical technologies. In an effort to improve such an important sector within the agriculture sector in Pakistan research has been carried out to better understand the capabilities and feasibility of leveraging Internet of Things based technologies, such as, microprocessors and microcontrollers within Pakistan's livestock production and management. The internet of Things can potentially allow for the scaling of small-scale rural livestock production to larger operations through cost effective and efficient livestock management through the application of IoT technologies. This paper discusses the architecture models of IoT based smart animal farms and delves into the pitfalls and advantages of applying IoT technologies in this sector. In this work we will explore the cheap sensors to monitor the internal activities of cattle farm with the aim of using these sensors as part of system to detect the important operations that need on the time response. This system should provide the feed and water as required, and control the temperature in sheds to protect the cattle being ill and on heat, and humidity level .internet connection used to connect these devices with smartphones or computers. In this paper we proposed the architecture model of IoT based smart animal farm.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.145-157
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• 2019

This study is to look at the influential factors associated with the acceptance intention of smart farm and suggest a proposal for spreading adoption of smart farms. The research questionnaire distributed to the farmers were used for the research analysis by statistical program SPSS v22.0 and Process macro v3.0. The technical characteristics of smart farm, which are availability, reliability and economic efficiency were selected as independent variables to analyze the influential factors on acceptance intention of smart farm and the mediating effect of effort expectation was observed. As a result, availability and economic efficiency have a positive(+) influence on acceptance intention and reliability have no influence on acceptance intention. And availability, reliability and economic efficiency have a positive(+) influence on effort expectation. Effort expectation mediates the relationship between the technical characteristics of smart farm and acceptance intention. The results of the study are expected to be utilized at the seeking direction of policy for potential adopters of smart farm, the training and consulting in actual field of smart farm.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.719-729
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• 2017

Recently, the field of agriculture has been gaining a new leap with the integration of ICT technology in agriculture. In particular, smart farms, which incorporate the Internet of Things (IoT) technology in agriculture, are in the spotlight. Smart farm technology collects and analyzes information such as temperature and humidity of the environment where crops are cultivated in real time using sensors to automatically control the devices necessary for harvesting crops in the control device, Environment. Although smart farm technology is paying attention as if it can solve everything, most of the research focuses only on increasing crop yields. This paper focuses on the development of a system architecture that can harvest high quality crops at the optimum stage rather than increase crop yields. In this paper, we have developed an architecture using apple trees as a sample and used the color information and weight information to predict the harvest time of apple trees. The simple board that collects color information and weight information and transmits it to the server side uses Arduino and adopts model-driven development (MDD) as development methodology. We have developed an architecture to provide services to PC users in the form of Web and to provide Smart Phone users with services in the form of hybrid apps. We also developed an architecture that uses beacon technology to provide orchestration information to users in real time.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.247-254
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• 2020

The socio-cultural and economic changes following the Fourth Revolution are driving the growth of the food tech industry. Korea's food tech industry is still focused on delivery apps and the smart farms, robot market including artificial intelligence are in its infancy. In the United States, alternative meat companies are already included in unicorn companies, while Korea, the fourth largest importer of beef, lacks alternative meat development. France, Europe's largest agricultural country, is focusing on Agtech. China has developed the Internet and online e-commerce market with the world's number one population. Korea also needs to change regulations that focus on the past industry and various food tech industries should be developed through political and business-driven research and investment.