• Title/Summary/Keyword: Agricultural control drone

Search Result 30, Processing Time 0.029 seconds

Development of Spray Calculation Algorithm Using the Pest Control Drones (농업용 방제드론의 방제면적 산출 알고리즘에 관한 연구)

  • Lim, Jin-Taek
    • Journal of Convergence for Information Technology
    • /
    • v.10 no.10
    • /
    • pp.135-142
    • /
    • 2020
  • In the recent farming industry, there is a growing diffusion of drones, which are recognized as a crucial technology of the 4 th industrial revolution to cope with aging. Especially, filming and pest control using drones are representative fields that have different age groups for obtaining a national license of multicopter that is a ultra-light flying device, and can create profits after getting a license. However, pest control technology using drones has different spray effects depending on levels of operational proficiency, since this highly relies on an operator's operating skills. It is anticipated that if this issue is supplemented, the use of drones for pest control in the farming industry will diversify. For analysis of spraying characteristics of agricultural pest control drones, this study aims to formulate effective spraying hours and effective spraying intervals and suggest an algorithm, which facilitates an accurate calculation of pest control area depending on the kinds of pest control drones. This algorithm can be used in the field of pest control by improving scatterling issues caused by drone flight methods of drone pest controllers and building an optimum pest control manual in future.

Pupal Drone Extracts for Anti-wrinkle and Skin-lightening Materials (수벌번데기 추출물의 주름개선 및 미백효과 구명)

  • Kim, Jung-Eun;Kim, Do-Ik;Koo, Hui-Yeon;Kim, Hyeon-Jin;Kim, Seong-Yeon;Lee, Yoo-Beom;Moon, Jae-Hak;Choi, Yong-Soo
    • Journal of Life Science
    • /
    • v.30 no.5
    • /
    • pp.428-433
    • /
    • 2020
  • In this study, we created pupal stage extracts of Apis mellifera L. drones for use in cosmetic materials. The effect of the drone pupae extract (DPE) on HDF cells was assessed for analysis of anti-wrinkle activity by collagen or collagenase gene expression, and the skin-lightening effect was studied by in vitro tyrosinase inhibition and B16F10 melanoma assay; the two cells were found to be non-cellular when the concentration of DPE was 100 ㎍/ml. Albutin concentration (positive control) in the whitening test was set at a capacity of 100 ug/ml and m-melanocyte stimulating hormone (α-MSH). A melanin-producing induction material was set at a concentration of 100 nM, and the expression of collagen type I and MMP1 collagenase was measured using HDF cells. MMP1 expression was seen to reduce in a concentration-dependent manner in treatment with DPE. Inhibiting melanin generation with B16F12 cells indicated a tendency to decrease in the DPE treatment group. Both L-Tyrosine and L-DOPA as DPE were used in an in vitro tyrosinase induction test to demonstrate the effects of tyrosinase suppression on concentrations. The higher the concentration of DPE, the greater the wrinkle reduction and whitening effect. In conclusion, it was found that DPE is an effective smoothing and whitening material by increasing collagen generation and inhibiting collagenase expression and reducing melanin production.

Study on the current direction of our country in accordance with the basic conditions for the commercialization of the UAV

  • Jo, Jong Deok;Lee, Chang Hee
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.8 no.4
    • /
    • pp.58-62
    • /
    • 2016
  • Shipping related services is attracting attention as a UAV (Unmanned Aerial Vehicle) application with the recent economy has been generally accepted drones. UAV of the existing military-driven logistics delivery, aerial photography, wireless Internet connection, broadcasting, disaster research, digital maps, transportation, advertising, meteorological, border surveillance, agricultural use, such as hobbies range of uses from up military are diverse and growing. The advantage of delivery drones seems to be an important feature of delivery of the goods, including labor-saving, long-distance transportation in cold weather. UAV is demanded by competitive performance development for commercialization. Privacy issues that may arise during the drone operation, ensuring marketability issues, control system, regulations, operational standards and specifications, etc. should be addressed. Development direction of Korea UAV based in current technology, regulation, and growth potential presented by deriving from the idea of 'GIF 2016 Gang-won Hackathon.

Preparation and Application of Cultivation Management Map Using Drone - Focused on Spring Chinese Cabbage - (드론 기반의 재배관리 지도 제작 및 활용방안 - 봄배추를 대상으로 -)

  • Na, Sang-il;Lee, Yun-ho;Ryu, Jae-Hyun;Lee, Dong-ho;Shin, Hyoung-sub;Kim, Seo-jun;Cho, Jaeil;Park, Jong-hwa;Ahn, Ho-yong;So, Kyu-ho;Lee, Kyung-do
    • Korean Journal of Remote Sensing
    • /
    • v.37 no.3
    • /
    • pp.637-648
    • /
    • 2021
  • In order to support the establishment of a farming plan, it is important to preemptively evaluate crop changes and to provide precise information. Therefore, it is necessary to provide customized information suitable for decision-making by farming stage through scientific and continuous monitoring using drones. This study was carried out to support the establishment of the farming plan for ground vegetable. The cultivation management map of each information was obtained from preliminary study. Three cultivation management maps include 'field emergence map', 'stress map' and 'productivity map' reflected spatial variation in the plantation by providing information in units of plants based on 3-dimensions. Application fields of the cultivation management map can be summarized as follows: detect miss-planted, replanting decision, fertilization, weeding, pest control, irrigation schedule, market quality evaluation, harvest schedule, etc.

Development of Fuzzy controller for battery cell balancing of agricultural drones (농업용 드론의 배터리 셀 밸런싱을 위한 퍼지제어기 개발)

  • Lee, Sang-Hyun
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.17 no.5
    • /
    • pp.199-208
    • /
    • 2017
  • Lithium polymer batteries are used in energy storage systems (ESS), electric vehicles (EVs), etc. due to their high safety, fast charging and long lifecycle, and now they are used in agricultural drones. However, when overcharging and overdischarging, the lithium-polymer battery is destroyed in the gap structure in the lithium-ion battery and the battery life is reduced. In order to prevent overcharge and overdischarge, uneven cell voltage Cell balancing system is needed. In this paper, a fuzzy controller suitable for nonlinear systems is proposed by detecting the unbalanced cells by detecting the voltage difference between charging and discharging of each cell, and suggesting the applied cell balancing algorithm. In this paper, we have designed the cell balancing of the battery pack of agricultural drones by fuzzy control and it is designed for equal control between cells. As a final result, we checked whether cell balancing is good, and when there are two cells, Cell balancing was confirmed. We tested whether it could be used for other products. As a result, we confirmed that cell balancing is good regardless of the number of cells used.

Control Standards of Three Major Insect Pests of Chinese Cabbage (Brassica campestris) Using Drones for Pesticide Application (농약살포용 드론을 이용한 배추 주요해충 3종의 방제기준 설정)

  • Choi, Duck-Soo;Ma, Kyung-Cheol;Kim, Hyo-Jeong;Lee, Jin-Hee;Oh, Sang-A;Kim, Seon-Gon
    • Korean journal of applied entomology
    • /
    • v.57 no.4
    • /
    • pp.347-354
    • /
    • 2018
  • In order to setting the control standard of Chinese cabbage pests using a drone, the downward wind speed, spraying width, and the number of falling particles and particle size were examined using a water sensitive paper with spray different heights (3, 4, 5 m) and flying speeds (3, 4 m/sec). Fore kinds of pesticides for aviation control were used to test the perfect lethal concentration and dose for major pests of Chinese cabbage such as Plutella xylostella, Spodoptera exigua and Spodoptera litura. The number of falling particles in spraying pesticides with drones was 80.5% on the upper side, 14.8% on the vertical side, and 4.7% on the back side. The number of falling particles as different spray heights were 3 m = 53, 4 m = 40 and $5m=39particles\;cm^{-2}$. The number of falling particles as different flying speeds were $3m\;sec^{-1}=62$ and $4m\;sec^{-1}=25particles\;cm^{-2}$. In the laboratory test, the perfect lethal concentration and dose of Plutella xylostella was chlorfenapyr SC (20 times, $0.5{\mu}l$) and bistrifluron chlorfenapyr SC (25 times, $0.5{\mu}l$). The perfect lethal concentration and dose of Spodoptera exigua was chlorfenapyr SC (20 times, $1{\mu}l$), bistrifluron chlorfenapyr SC (20 times, $1{\mu}l$), and chlorfenapyr SC (20 times, $1{\mu}l$) and bistrifluron chlorfenapyr SC (20 times, $0.5{\mu}l$) for Spodoptera litura. Therefore, the main pest control method of Chinese cabbage using drones is 20 times diluted chlorphenapyr SC or bistrifluoruron-chlorphenapyr SC, sprayed at 3 m height by $3msec^{-1}$ of going speed. This spraying method will be effective for control of Chinese cabbage pest.

Real-Time Soil Humidity Monitoring Based on Sensor Network Using IoT (IoT를 사용한 센서 네트워크 기반의 실시간 토양 습도 모니터링)

  • Kim, Kyeong Heon;Kim, Hee-Dong
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
    • /
    • v.35 no.5
    • /
    • pp.459-465
    • /
    • 2022
  • This paper reports a method to use a wireless sensor network deployed in the field to real-time monitor soil moisture, warning when the moisture level reaches a specific value, and wirelessly controlling an additional device (LED or water supply system, etc.). In addition, we report all processes related to wireless irrigation system, including field deployment of sensors, real-time monitoring using a smartphone, data calibration, and control of additional devices deployed in the field by smartphone. A commercially available open-source Internet of Things (IoT) platform, NodeMCU, was used, which was combined with a 9V battery, LED and soil humidity sensor to be integrated into a portable prototype. The IoT-based soil humidity sensor prototype deployed in the field was installed next to a tree for on-site demonstration for the measurement of soil humidity in real-time for about 30 hours, and the measured data was successfully transmitted to a smartphone via Wifi. The measurement data were automatically transmitted via e-mail in the form of a text file, stored on the web, followed by analyses and calibrations. The user can check the humidity of the soil real-time through a personal smartphone. When the humidity of a soil reached a specific value, an additional device, an LED device, placed in the field was successfully controlled through the smartphone. This LED can be easily replaced by other electronic devices such as water supplies, which can also be controlled by smartphones. These results show that farmers can not only monitor the condition of the field real-time through a sensor monitoring system manufactured simply at a low cost but also control additional devices such as irrigation facilities from a distance, thereby reducing unnecessary energy consumption and helping improve agricultural productivity.

Development and Verification of an AI Model for Melon Import Prediction

  • KHOEURN SAKSONITA;Jungsung Ha;Wan-Sup Cho;Phyoungjung Kim
    • Journal of the Korea Society of Computer and Information
    • /
    • v.28 no.7
    • /
    • pp.29-37
    • /
    • 2023
  • Due to climate change, interest in crop production and distribution is increasing, and attempts are being made to use bigdata and AI to predict production volume and control shipments and distribution stages. Prediction of agricultural product imports not only affects prices, but also controls shipments of farms and distributions of distribution companies, so it is important information for establishing marketing strategies. In this paper, we create an artificial intelligence prediction model that predicts the future import volume based on the wholesale market melon import volume data disclosed by the agricultural statistics information system and evaluate its accuracy. We create prediction models using three models: the Neural Prophet technique, the Ensembled Neural Prophet model, and the GRU model. As a result of evaluating the performance of the model by comparing two major indicators, MAE and RMSE, the Ensembled Neural Prophet model predicted the most accurately, and the GRU model also showed similar performance to the ensemble model. The model developed in this study is published on the web and used in the field for 1 year and 6 months, and is used to predict melon production in the near future and to establish marketing and distribution strategies.

Advances, Limitations, and Future Applications of Aerospace and Geospatial Technologies for Apple IPM (사과 IPM을 위한 항공 및 지리정보 기술의 진보, 제한 및 미래 응용)

  • Park, Yong-Lak;Cho, Jum Rae;Choi, Kyung-Hee;Kim, Hyun Ran;Kim, Ji Won;Kim, Se Jin;Lee, Dong-Hyuk;Park, Chang-Gyu;Cho, Young Sik
    • Korean journal of applied entomology
    • /
    • v.60 no.1
    • /
    • pp.135-143
    • /
    • 2021
  • Aerospace and geospatial technologies have become more accessible by researchers and agricultural practitioners, and these technologies can play a pivotal role in transforming current pest management practices in agriculture and forestry. During the past 20 years, technologies including satellites, manned and unmanned aircraft, spectral sensors, information systems, and autonomous field equipment, have been used to detect pests and apply control measures site-specifically. Despite the availability of aerospace and geospatial technologies, along with big-data-driven artificial intelligence, applications of such technologies to apple IPM have not been realized yet. Using a case study conducted at the Korea Apple Research Institute, this article discusses the advances and limitations of current aerospace and geospatial technologies that can be used for improving apple IPM.

Utilization of Smart Farms in Open-field Agriculture Based on Digital Twin (디지털 트윈 기반 노지스마트팜 활용방안)

  • Kim, Sukgu
    • 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.

  • PDF