• Title/Summary/Keyword: Agricultural data

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Fuel Consumption Prediction and Life Cycle History Management System Using Historical Data of Agricultural Machinery

  • Jung Seung Lee;Soo Kyung Kim
    • Journal of Information Technology Applications and Management
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    • v.29 no.5
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    • pp.27-37
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    • 2022
  • This study intends to link agricultural machine history data with related organizations or collect them through IoT sensors, receive input from agricultural machine users and managers, and analyze them through AI algorithms. Through this, the goal is to track and manage the history data throughout all stages of production, purchase, operation, and disposal of agricultural machinery. First, LSTM (Long Short-Term Memory) is used to estimate oil consumption and recommend maintenance from historical data of agricultural machines such as tractors and combines, and C-LSTM (Convolution Long Short-Term Memory) is used to diagnose and determine failures. Memory) to build a deep learning algorithm. Second, in order to collect historical data of agricultural machinery, IoT sensors including GPS module, gyro sensor, acceleration sensor, and temperature and humidity sensor are attached to agricultural machinery to automatically collect data. Third, event-type data such as agricultural machine production, purchase, and disposal are automatically collected from related organizations to design an interface that can integrate the entire life cycle history data and collect data through this.

Exploring Enhancements of Data Industry Competitiveness in the Agricultural Sector (농업 부문 데이터 산업 경쟁력 제고 방안)

  • Choi, Ha-Yeon;Im, Ye-Rin;Kang, Seung-Yong;Kang, Seung-Yong;Yoo, Do-il
    • Journal of Korean Society of Rural Planning
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    • v.29 no.4
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    • pp.137-152
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    • 2023
  • Data is indispensable for digital transformation of agriculture with the development of innovative information and communication technology (ICT). In order to devise and prioritize strategies for enhancing data competitiveness in the agricultural sector, we employed an Analytic Hierarchy Process (AHP) analysis. Drawing from existing research on data competitiveness indicators, we developed a three-tier decision-making structure reflecting unique characteristics of the agricultural sector such as farmers'awareness of the data industry or awareness of agriculture among data workers. AHP survey was administered to experts from both agricultural and non-agricultural sectors with a high understanding of data. The overall composite importance, derived from the respondents, was rated in the following order: 'Employment Support', 'Data Standardization', 'R&D Support', 'Start-up Ecosystem Support', 'Relaxation of Regulations', 'Legislation', and 'Data Analytics and Utilization Technology'. In the case of experts in the agricultural sector, 'Employment Support' was ranked as the top priorities, and 'Legislation', 'Undergrad and Grad Education', and 'In-house Training' were also regarded as highly important. On the other hand, experts in the non-agricultural sector perceived 'Data Standardization' and 'Relaxation of Regulations' as the top two priorities, and 'Data Center' and 'Open Public Data' were also highly rated.

Construction of Integrated Agricultural Statistical System Architecture for Effective Policy (농업정책 실효성 증대를 위한 농업통계시스템 아키텍처 구축)

  • Lee, Min-Soo;Chae, Young-Chan;Hong, Hee-Yeon;Kim, Sang-Ho;Kim, Jeong-Seop
    • Journal of Korean Society of Rural Planning
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    • v.11 no.4 s.29
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    • pp.75-91
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    • 2005
  • This study designs an integrated data architecture to systematically manage the agricultural statistics database. Managing the agricultural statistics is important since it provides data for policies and decision making for agribusinesses. Ministry of Agriculture and the National Statistical Office collect the basic agricultural statistic data which provides the basis of logical decision making and agricultural policies. However, the agricultural statistic data has not well been used. The data has not been consistently collected nor managed. The raw data has not been organized nor processed to meet various demands. The needs has been arisen for a consistent agricultural statistics system to increase the relevance, accessibility, and efficiency of data for various users. There are massive amount of data accumulated over a long time period. Introducing the new system and reorganizing the data will bear large risks. A systematic method is required to reduce the risks in planing, building, and maintaining the database without hindering administration. This study provides a design of the agricultural statistics system architecture based on the user requirement analysis (URA) and similar systems abroad. We have also build a prototype to check the implementability of the system design.

Construction of Agricultural Meteorological Data by the New Climate Change Scenario for Forecasting Agricultural Disaster - For 111 Agriculture Major Station - (농업재해 예측을 위한 신 기후변화 시나리오의 농업기상자료 구축 - 111개 농업주요지점을 대상으로 -)

  • Joo, Jin-Hwan;Jung, Nam-Su;Seo, Myung-Chul
    • Journal of The Korean Society of Agricultural Engineers
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    • v.55 no.6
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    • pp.87-99
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    • 2013
  • For analysis of climate change effects on agriculture, precise agricultural meteorological data are needed to target period and site. In this study, agricultural meteorological data under new climate change scenario (RCP 8.5) are constructed from 2011 to 2099 in 111 agriculture major station suggested by Rural Development Administration (RDA). For verifying constructed data, comparison with field survey data in Suwon shows same trend in maximum temperature, minimum temperature, average temperature, and precipitation in 2011. Also comparison with normals of daily data in 2025, 2055, and 2085 shows reliability of constructed data. In analysis of constructed data, we can calculate sum of days over temperature and under temperature. Results effectively show the change of average temperature in each region and odd days of precipitation which means flood and dry days in target region.

Quality Control on Water-level Data in Agricultural Reservoirs Considering Filtering Methods (필터링 기법을 이용한 농업용저수지 수위자료의 품질관리 방안)

  • Kim, Kyung-hwan;Choi, Gyu-hoon;Jung, Hyoung-mo;Joo, Donghyuk;Na, Ra;Choi, Eun-hyuk;Kwon, Jae-Hwan;Yoo, Seung-Hwan
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.5
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    • pp.83-93
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    • 2021
  • Agricultural reservoirs are important facilities for storing or managing water for the purpose of securing agricultural water, creating and expanding agricultural production bases, and using them to increase agricultural production. In particular, the Korea Rural Community Corporation (KRC) manages agricultural reservoirs scattered across the country, and officially recognizes and distributes hydrological data to increase their public utilization and aims to improve the value of water resources. Data on the water level of agricultural reservoirs are important. However, errors such as missing values and outliners limit utilization of the data in various fields of research and industry. Therefore, water quality data measures should be devised to increase reliability. this study categorized different error types and looked at automatic correction methods to enhance the reliability of the vast hydrological data. In addition, the water level data corrected from errors were compared to the reference hydrologic data through expert judgment in accordance with the quality control procedure, and the most appropriate measures were verified. As KRC manages more agricultural reservoirs than any other institution, the proposed method of efficient and automatic water level data correction in this study is expected to increase the availability and reliability of the hydrological data.

Development of A Pilot Android Application for Location-based Mobile Agricultural Information System (위치기반 모바일 농업정보시스템 구축을 위한 안드로이드 애플리케이션 시험 개발)

  • Kim, Sang Min;Jang, Min-Won
    • Journal of Korean Society of Rural Planning
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    • v.20 no.4
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    • pp.277-284
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    • 2014
  • Recently the use of smart phones and mobile devices is increasing rapidly, data search and retrieval in the mobile environments are generalized. There are only few mobile applications available in the area of agriculture while huge amount of new applications are developed and uploaded. The purpose of this study was to develop the android based mobile application for providing agricultural infrastructure and disaster information. The mobile application was designed through the database establishment and management system, server management system, and mobile application development. The database is composed of weather data, agricultural infrastructure data, and agricultural disaster data. By developing the mobile application which provides agricultural infrastructure information, it is expected to improve the accessibility to agricultural information and mitigate the agricultural disaster damages.

Web-Based Data Processing and Model Linkage Techniques for Agricultural Water-Resource Analysis (농촌유역 물순환 해석을 위한 웹기반 자료 전처리 및 모형 연계 기법 개발)

  • Park, Jihoon;Kang, Moon Seong;Song, Jung-Hun;Jun, Sang Min;Kim, Kyeung;Ryu, Jeong Hoon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.57 no.5
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    • pp.101-111
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    • 2015
  • Establishment of appropriate data in certain formats is essential for agricultural water cycle analysis, which involves complex interactions and uncertainties such as climate change, social & economic change, and watershed environmental change. The main objective of this study was to develop web-based Data processing and Model linkage Techniques for Agricultural Water-Resource analysis (AWR-DMT). The developed techniques consisted of database development, data processing technique, and model linkage technique. The watershed of this study was the upper Cheongmi stream and Geunsam-Ri. The database was constructed using MS SQL with data code, watershed characteristics, reservoir information, weather station information, meteorological data, processed data, hydrological data, and paddy field information. The AWR-DMT was developed using Python. Processing technique generated probable rainfall data using non-stationary frequency analysis and evapotranspiration data. Model linkage technique built input data for agricultural watershed models, such as the TANK and Agricultural Watershed Supply (AWS). This study might be considered to contribute to the development of intelligent watercycle analysis by developing data processing and model linkage techniques for agricultural water-resource analysis.

Development of Agricultural Drought Assessment Approach Using SMAP Soil Moisture Footprints (SMAP 토양수분 이미지를 이용한 농업가뭄 평가 기법 개발)

  • Shin, Yongchul;Lee, Taehwa;Kim, Sangwoo;Lee, Hyun-Woo;Choi, Kyung-Sook;Kim, Jonggun;Lee, Giha
    • Journal of The Korean Society of Agricultural Engineers
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    • v.59 no.1
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    • pp.57-70
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    • 2017
  • In this study, we evaluated daily root zone soil moisture dynamics and agricultural drought using a near-surface soil moisture data assimilation scheme with Soil Moisture Active & Passive (SMAP, $3km{\times}3km$) soil moisture footprints under different hydro-climate conditions. Satellite-based LANDSAT and MODIS image footprints were converted to spatially-distributed soil moisture estimates based on the regression model, and the converted soil moisture distributions were used for assessing uncertainties and applicability of SMAP data at fields. In order to overcome drawbacks of the discontinuity of SMAP data at the spatio-temporal scales, the data assimilation was applied to SMAP for estimating daily soil moisture dynamics at the spatial domain. Then, daily soil moisture values were used to estimate weekly agricultural drought based on the Soil Moisture Deficit Index (SMDI). The Yongdam-dam and Soyan river-dam watersheds were selected for validating our proposed approach. As a results, the MODIS/SMAP soil moisture values were relatively overestimated compared to those of the TDR-based measurements and LANDSAT data. When we applied the data assimilation scheme to SMAP, uncertainties were highly reduced compared to the TDR measurements. The estimated daily root zone soil moisture dynamics and agricultural drought from SMAP showed the variability at the sptio-temporal scales indicating that soil moisture values are influenced by not only the precipitation, but also the land surface characteristics. These findings can be useful for establishing efficient water management plans in hydrology and agricultural drought.

Developing a Web-based System for Computing Pre-Harvest Residue Limits (PHRLs)

  • Chang, Han Sub;Bae, Hey Ree;Son, Young Bae;Song, In Ho;Lee, Cheol Ho;Choi, Nam Geun;Cho, Kyoung Kyu;Lee, Young Gu
    • Agribusiness and Information Management
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    • v.3 no.1
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    • pp.11-22
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    • 2011
  • This study describes the development of a web-based system that collects all data generated in the research conducted to set pre-harvest residue limits (PHRLs) for agricultural product safety control. These data, including concentrations of pesticide residues, limit of detection, limit of quantitation, recoveries, weather charts, and growth rates, are incorporated into a database, a regression analysis of the data is performed using statistical techniques, and the PHRL for an agricultural product is automatically computed. The development and establishment of this system increased the efficiency and improved the reliability of the research in this area by standardizing the data and maintaining its accuracy without temporal or spatial limitations. The system permits automatic computation of the PHRL and a quick review of the goodness of fit of the regression model. By building and analyzing a database, it also allows data accumulated over the last 10 years to be utilized.

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Study on Establishment of the Greenhouse Environment Monitoring System for Crop Growth Monitoring (작물 생식 모니터링을 위한 온실환경 모니터링 시스템 구축연구)

  • Kim, Won-Kyung;Cho, Byeong-Hyo;Hong, Youngki;Choi, Won-Sik;Kim, Kyoung-Chul
    • Journal of the Korean Society of Industry Convergence
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    • v.25 no.3
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    • pp.349-356
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    • 2022
  • Currently, the agricultural population in Korea indicates a decreasing and aging orientation. As the population of farm labor continues to decline, so farmers are feeling the pressure to be stable crop production. To solve the problem caused by the decreasing of farm labor, it is necessary to change over to "Digital agriculture". Digital agriculture is tools that digitally collect, store, analyze, and share electronic data and/or information in agriculture, and aims to integrate the several digital technologies into crop and livestock management and other processes in agriculture fields. In addition, digital agriculture can offer the opportunity to increase crop production, save costs for farmer. Therefore, in this study, for data-based Digital Agriculture, a greenhouse environment monitoring system for crop growth monitoring based on Node-RED, which even beginners can use easily, was developed, and the implemented system was verified in a hydroponic greenhouse. Several sensors, such as temperature, humidity, atmospheric pressure, CO2, solar radiation, were used to obtain the environmental data of the greenhouse. And the environmental data were processed and visualized using Node-RED and MariaDB installed in rule.box digital. The environment monitoring system proposed in this study was installed in a hydroponic greenhouse and obtained the environmental data for almost two weeks. As a result, it was confirmed that all environmental data were obtained without data loss from sensors. In addition, the dashboard provides the names of installed sensors, real time environmental data, and changes in the last three days for each environmental data. Therefore, it is considered that farmers will be able to easily monitor the greenhouse environment using the developed system in this study.