Design of Big Data-based Greenhouse Environment Data Consulting System for Improving Crop Quality

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1 , pp Design of Big Data-based Greenhouse Environment Data Consulting System for Improving Crop Quality Seongjin Kim, Hyun Yoe 1 Department of Information and Communication Engineering, Sunchon National University, Korea {prava88, Abstract. Recently, as for agricultural technologies in South Korea, these researches on smart greenhouses and smart farms with ICT technology applied are being carried out in pursuit of improvements in both productivity and quality of crops. Such ICT technology is now actually being applied to real farming, and that builds up so many pieces of environmental data information. By utilizing all that information accumulated for long, this paper first collects environmental data information on a region basis to cultivate crops of the best quality and then by practicing the gathered information to actual farming, the study offers a greenhouse environmental data consulting system that would help the most optimized growth of crops. The system to be proposed is designed to have an environment sensor to gather data, an embedded server and HDFS to store and process data as well as a Web application to provide greenhouse control and service. 1 Introduction In terms of the farming industry in South Korea, they are entering a stage of graying as a whole which is consequently causing a work shortage in every part of the industry. Farmers earn less than before, and that is bringing about financial problems. If such problems are not properly handled constantly, when any unexpected tragedies occur such as natural disasters by external surroundings, the lack of agricultural technologies will only aggravate harm and damage. That is why this paper believes that diverse areas of the farming industry such as the economy, the technology and others should find ways to enhance the quality of life and that the industry must resolve the financial issues by increasing productivity via reductions in maintenance costs and others. In addition, now, the conclusion of the FTA is facilitating the globalization of the distribution industry, and that is what encourages this paper to argue even more strongly for the necessity of strategies for development and advances in agricultural technologies targeting the improvement in competitiveness of the farming industry in South Korea. Regarding the Netherlands, one of the advanced countries in the field of agricultural business, their territory may be small in size and yet, they are recognized 1 Corresponding author ISSN: ASTL Copyright 2015 SERSC

2 as the second-largest agricultural exporter in the world (75.4 billion dollars as of 2012) and as to the labor power engaged in the farming industry in 2012, it was reported to be 1,610,000 individuals in figures. The population is smaller than 2,792,564 farming labourers in South Korea by 57%, and that is only a good indicator to prove the reputation of the Netherlands as a developed nation.[2] In order to realize even a higher level of crop quality, the Netherlands makes use of an automation system which had been built upon the integration of multiple information communication technologies such as environmental information data collecting methods that would use environmental researches and sensors including several others. The story is very much similar with South Korea, and many farmers in the country are surely capable of selecting and controlling environmental data using ICT but still, it is somewhat difficulty for those farmers to share what they are able to do with each other. Add to that, in South Korea, each of the regions has these external environments noticeable different from one another and therefore, even if the farmers in South Korea cultivate the same crops, they end up producing the crops in very much different sizes and quality. Such problem should be carefully investigated, and South Korea will finally find ways to solve the problem if they create a system to help the farmers share what they are capable of with each other. In order to work the problem out, this paper aims to propose a big data-based greenhouse environmental data consulting system for improvements in crop quality. With the help of this to-be-offered system, the paper analyzes environmental information data selected from each of the farmers as a big data and through the analysis, regional external environmental data as well as this particular environment proper enough for cultivation of a certain crop are gained, and that will increase possibilities of improvements in crop quality and increase in productivity. Moreover, the system will reduce use of unnecessary energy which has been carelessly wasted, and that will result in decrease of production costs. The paper develops as follows. Chapter 2 explains relevant researches that had once talked about the system. In Chapter 3, how to design the system is discussed. Last but not least, in the conclusion, the paper finishes its research. 2 Related Research 2.1 Rural development administration Korean Smart Farm In regard to the Korean Smart Farm Project being promoted by Rural Development Administration, they first set an ICT-based optimum growth environment in these fields of controlled horticulture, pig farming and others that have a strong possibility of being well integrated with ICT and then, by applying the advanced technology, they decrease management costs as increasing quality and productivity of crops. Smart Farm automatically measures and analyzes internal and external environments of greenhouses and growth of crops, and it is after all understood as a science technology-and-information communication-combined agricultural management Copyright 2015 SERSC 183

3 method that would conduct remote controls onto growth and development by manipulating an optimized environment and keeping records of the environment based on the big data. Fig. 1. Farm greenhouses and hydroponic internal environment control system Moreover, Smart Farm automatically measures growth and development environments of key crops on a stage basis and designs a precise control model. For supporting consultations, Rural Development Administration will also study and develop core technologies such as the optimized growth and development model for greenhouse crops, animal welfare pigsty management model and others. 2.1 Europe's crop production monitoring system Project DEMETER in Europe uses a premonitory climate model ensemble and forecasts seasonal climates. The forecast produces meteorological elements, and they are applied to a crop productivity model. That way, Project DEMETER can test usefulness and performance of a crop productivity forecast system. Not only that, the project is told to have an advantage in that it offers additional information such as anomaly, uncertainty and others of these outcomes produced by the crop productivity system. Fig. 2. Crop Production Monitoring System 184 Copyright 2015 SERSC

4 3 System Design The big data-based green environmental data consulting system to improve crop quality presented by this paper is designed as Fig.3 and basically, the system is categorized into these areas of data collecting, data saving and processing and data analyzing including visualization. Fig. 3. System Configuration As for the data collecting area, these environmental sensors to gather greenhouse environmental information data that would affect growth and development of greenhouse crops in each region such as temperature, humidity, illumination, CO2 and others are required, and collected data is managed by the embedded server so that the data is transmitted to greenhouses in each of the regions. The data saving and processing area consists of these embedded servers installed in each greenhouse and HDFS (Hadoop Distributed File System) as well which stores and handles big data collected from the greenhouses in each of the regions. The data analyzing and visualization area works with a Web application that would monitor a greenhouse environment in each of the regions as checking crop quality at the same time. The embedded servers are installed in greenhouses in each of the regions, and as receiving and processing environment data gathered from the greenhouses real time, they maximize storage and processing functions of HDFS. Environmental data selected from HDFS is undergone separate storage and processing work and quality of a crop is observed. A Web application program is placed so that a user is provided with useful information and services. The user is given regional environmental data information via a Web or mobile device, and one can understand proper temperatures for his crops depending on different quality and he can also actually apply the temperatures to his own greenhouse. Add to that, the Web application program sends out environmental data and crop conditions gathered from the user s greenhouse to the user real time via the application server. Copyright 2015 SERSC 185

5 Fig. 4. System Process A flow chart of the proposed system is presented in Fig.4. Data selected from regional greenhouse environmental sensors is transmitted to the sensor embedded servers installed in each of the greenhouses, and the sensor embedded servers process the collected data before sending it to HDFS. Based on the collected data, HDFS checks environmental information and conditions of crops and after analyzing if the crops are best in quality as described in data at present, it sends out results. When an analysis does not say that the crops are in the best conditions, it saves data inside itself but when the crops look most satisfactory, the data is transmitted to a client embedded server. The client embedded server delivers environmental data information to an user after properly processing the information for easy viewing of an user. The user takes care of one s greenhouse based on the transmitted environmental data and saves new data gathered in the greenhouse again in HDFS. 4 Conclusion This paper uses a big data technology which is told to be highly practical as a convergence technology of today and designs a greenhouse environmental data consulting system that would help every user to cultivate the best-quality crops referring to optimized crop growth and development environmental data gathered from greenhouses. The proposed big data-based greenhouse environmental data consulting system to improve crop quality consists of an environmental sensor that collects regional greenhouse environment data, a regional embedded server and HDFS (Hadoop Distributed File System) that store and process data and an application that reports conditions of crop quality, environmental data information as well as service. In addition, as sending out environmental data information real time through the embedded server installed in each of the regions, the system contributes to smooth performance of HDFS. 186 Copyright 2015 SERSC

6 The paper believes that the systems presented in this study will facilitate cultivation of crops in the most satisfactory quality, and if the system is successfully applied to greenhouses, not only will the crop productivity and the crop quality be enhanced but unnecessary waste of resources will be also reduced. Acknowledgments. "This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the C-ITRC (Convergence Information Technology Research Center) (IITP-2015-H ) supervised by the IITP(Institute for Information & communications Technology Promotion)" References 1. Seong-Eun Yang, Hwang-Kyu Choi, Chang-Yeol Choi, Design and Implementation of Vehicle Route Tracking System using Hadoop-Based Bigdata Image Processing, Journal of Digital Contents Society Vol. 14 No. 4 Dec. 2013(pp ) 2. Seong-Chan Choi, Min-Woo Ryu, Nam Jin, Jae-Ho Kim, Internet of Things platform and service trends, Journal of The Korean Institute of Communication Sciences) Vol.31 No.4 [2014] 3. Jeong-Hwan Hwang, Hyun Yoe, A Study on the Greenhouse Integrated Control System based on Big Data Platform, Department of Information and Communication Engineering The Graduate School of Sunchon National University, Agricultural Science Library, 5. Korea Meteorological Administration, METEOROLGICAL TECHNOLOGY & POLICY, 2012 Copyright 2015 SERSC 187

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