• Journal of Advanced Technology Convergence
• /
• v.2 no.1
• /
• pp.1-7
• /
• 2023

Recently, there have been increasing interests in researches to apply wireless communication technologies for smart farm. This paper introduces the problems in the smart farm for the outdoor culture and technical considerations to solve the problems. As candidate technologies, this paper selects LoRa, Sigfox, NB-IoT, and Wi-Fi and then determines that LoRa is a suitable technology based on the CAPEX, coverage, transmission rate, battery, and the price. To provide technical analysis, this paper introduces technologies related to the physical and medium access control (MAC) layers as well as the security. Specifically, this paper includes the modulation technology in the physical layer, Class (Class A, B, and C) based protocol operations in MAC layer, and security architecture based on the LoRa version.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2020.11a
• /
• pp.5-5
• /
• 2020

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2023.04a
• /
• pp.7-7
• /
• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Food Science and Preservation
• /
• v.30 no.3
• /
• pp.483-491
• /
• 2023

This study aimed to compare the bioactive compounds in Centella asiatica (C. asiatica) cultivated in a smart farm and a field and their effects on human keratinocyte cells. C. asiatica was collected in Jeju-do, Korea, and cultured in a smart farm and a field. The main bioactive compounds in the two differentially cultured C. asiatica were identified, and their activation in keratinocytes were assessed. Amplification and sequencing of the internal transcribed spacer (ITS) DNA in the nucleus and psbA-H DNA in the chloroplast were performed for species analysis. A comparison of DNA of plants reported in the NCBI GenBank was performed. The ITS DNA and psbA-H DNA sequences of C. asiatica cultivated in a smart farm and a field were consistent with No. MH768338.1 and No. JQ425422.1, respectively. Analysis of the triterpenes was performed using high performance liquid chromatography (HPLC) and as a result, C. asiatica cultured in a smart farm had more triterpenes than those cultured in a field. The effects of C. asiatica grown in a smart farm on cell proliferation and scratch recovery in HaCaT cells were greater than those grown in a field. These results suggest that C. asiatica cultivated in a smart farm can be effectively utilized as a health functional food.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.58 no.4
• /
• pp.30-37
• /
• 2016

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.4
• /
• pp.695-702
• /
• 2020

Recently, as research on smart farms has been actively conducted, indoor environment control, such as a green house, has reached a high level. However, In the field of forestry where cultivation is carried out in outdoor, the use of ICT is still insufficient. In this paper, we propose LPWA-based forest growth environment collection and big data analysis system using ICT technology. The proposed system collects and transmits the field cultivation environment data to the server using small solar power generation and LPWA technology based on the oneM2M architecture. The transmitted data is constructed as big data on the server and utilizes it to predict the production and quality of forest products. The proposed system is expected to contribute to the production of low-cost, high-quality crops through the fusion of renewable energy and smart farms. In addition, it can be applied to other industrial fields that utilize the oneM2M architecture and monitoring the growth environment of agricultural crops in the field.

• Proceedings of the Plant Resources Society of Korea Conference
• /
• 2022.09a
• /
• pp.84-84
• /
• 2022

백리향(Thymus quinquecostatus)은 꿀풀과의 낙엽반관목으로 국내에서 자생하는 허브 식물 중 하나이다. 백리향은 특유의 좋은 향기 및 항산화, 항염증, 항균, 미백 등의 효능을 가지는 각종 폴리페놀 성분을 함유하고 있어 의약품이나 기능성 식품, 화장품의 천연 소재 원료로 활용되고 있다. 국내에서 백리향은 재배 환경에 맞추어 주로 고산지대의 노지에서 재배되고 있다. 노지 재배는 지역, 시기, 기후 등의 외부환경에 영향을 받아서 백리향의 유효성분, 품질 및 생산성을 안정적으로 유지하기 어렵다는 한계를 가지고 있다. 따라서 본 연구에서는 스마트팜 시스템을 활용하여 백리향의 유효 성분 등을 안정적으로 얻기 위한 생장조건을 탐색하기 위해 4종의 Light Emitting Diode(LED) 광원과 4종의 토양 조성에 따라서 백리향의 생육조건을 수행하였다. LED는 white, purple, RGB1, RGB2를 사용하였으며, 토양은 상토:펄라이트 비율(상토, 5:1, 3:1, 1:1)로 조성하여 백리향 묘목을 이식한 뒤 생장과 개화시기를 분석하였다. 재배환경은 백리향 재배지의 기상 데이터를 참고하여 동일하게 설정하였으며, 총 8주 동안 생육상태를 관찰하였다. 연구 결과 백리향 재배 4주차에 일부 개체에서 봉오리가 올라오며 개화를 시작하였으며, 8주차에는 대부분의 조건에서 개화를 관찰할 수 있었다. 백리향의 지상부 면적을 비교한 결과 가장 우수한 생장을 보이는 조건은 토양은 3(상토):1(펄라이트) 비율로 분석되었다. 따라서 이번 연구 결과를 바탕으로 백리향 재배에 스마트팜 농업 기술을 활용한다면 기존 노지 재배 한계를 보완하여 안정적이고 지속적인 백리향을 생산할 수 있을것으로 기대된다.

• Journal of the Korea Convergence Society
• /
• v.9 no.7
• /
• pp.63-68
• /
• 2018

Research on smart farms centering on greenhouse cultivation is actively under way due to the decrease in agriculture population and aging, but in the case of vegetables such as vegetables, outdoor cultivation is 70%. Therefore, there is a need to improve productivity and prevent soil contamination by automating, cultivating, and intelligentizing the outdoor cultivation of agriculture crops. In this paper, we show the case of establishing a outdoor production system using the Internet of things and define the environmental variables in the outdoor production system. By measuring soil temperature, water content, electrical conductivity and acidity through sensors, LoRa communication module transmits the information to the outdoor production system. The outdoor production system controls the amount of fertilizer and the volume of water based on this sensor data. We have developed a system that manages a wide range of crops using LoRa technology, which is a suitable communication method for cultivating crops, and manages production volume and sales performance.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.6
• /
• pp.1373-1378
• /
• 2018

In order to solve the problems such as reduction of agriculture population, aging and declining of grain self sufficiency rate, agriculture ICT convergence technology utilizing IoT technology is actively being developed. Agricultural ICT technology only concentrates on facility houses, and there is no automated control system in the field of cultivation. In this paper, we propose an irrigation control system that automatically controls the solenoid valves and water pumps in a large area with Lora wireless communication. The proposed system does not require a separate power source by using a small solar panel, and it is very convenient to install and operate supporting wireless auto setup by plug-and-play method. Therefore, it is expected that it will contribute to the reduction of labor force, quality of agricultural products, and productivity improvement.

• Smart Media Journal
• /
• v.12 no.10
• /
• pp.47-54
• /
• 2023

As understanding sudden climate change and agricultural productivity becomes increasingly important due to global warming, soil moisture prediction is emerging as a key topic in agriculture. Soil moisture has a significant impact on crop growth and health, and proper management and accurate prediction are key factors in improving agricultural productivity and resource management. For this reason, soil moisture prediction is receiving great attention in agricultural and environmental fields. In this paper, we collected and analyzed open field environmental data using a pilot field through random forest, a machine learning algorithm, obtained the correlation between data characteristics and soil moisture, and compared the actual and predicted values of soil moisture. As a result of the comparison, the prediction rate was about 92%. It was confirmed that the accuracy was . If soil moisture prediction is carried out by adding crop growth data variables through future research, key information such as crop growth speed and appropriate irrigation timing according to soil moisture can be accurately controlled to increase crop quality and improve productivity and water management efficiency. It is expected that this will have a positive impact on resource efficiency.