• Journal of Biosystems Engineering
• /
• v.41 no.4
• /
• pp.408-417
• /
• 2016

Purpose: Yield monitoring systems are an essential component of precision agriculture. They indicate the spatial variability of crop yield in fields, and have become an important factor in modern harvesters. The objective of this paper was to review research trends related to yield monitoring sensors for grain crops. Methods: The literature was reviewed for research on the major sensing components of grain yield monitoring systems. These major components included grain flow sensors, moisture content sensors, and cutting width sensors. Sensors were classified by sensing principle and type, and their performance was also reviewed. Results: The main targeted harvesting grain crops were rice, wheat, corn, barley, and grain sorghum. Grain flow sensors were classified into mass flow and volume flow methods. Mass flow sensors were mounted primarily at the clean grain elevator head or under the grain tank, and volume flow sensors were mounted at the head or in the middle of the elevator. Mass flow methods used weighing, force impact, and radiometric approaches, some of which resulted in measurement error levels lower than 5% ($R^2=0.99$). Volume flow methods included paddle wheel type and optical type, and in the best cases produced error levels lower than 3%. Grain moisture content sensing was in many cases achieved using capacitive modules. In some cases, errors were lower than 1%. Cutting width was measured by ultrasonic distance sensors mounted at both sides of the header dividers, and the errors were in some cases lower than 5%. Conclusions: The design and fabrication of an integrated yield monitoring system for a target crop would be affected by the selection of a sensing approach, as well as the layout and mounting of the sensors. For accurate estimation of yield, signal processing and correction measures should be also implemented.

• Korean Journal of Soil Science and Fertilizer
• /
• v.46 no.2
• /
• pp.73-80
• /
• 2013

Due to the fact that possible risk associated with soil-crop-food chain transfer, metal contamination in croplands has become a major topic of wide concern. Accumulation of toxic metals in edible parts of crops grown in contaminated soils has been reported from number of crops including rice, soybean, wheat, maize, and vegetables. Therefore, in order to ensure food safety, measures are needed to be taken in mitigating metal pollution and subsequent uptake by crop plants. Present paper critically reviewed some of the cost effective remediation techniques used in minimizing metal uptake by crops grown in contaminated soils. Liming with different materials such as limestone ($CaCO_3$), burnt lime (CaO), slaked lime [$Ca(OH)_2$], dolomite [$CaMg(CO_3)_2$], and slag ($CaSiO_3$) has been widely used because they could elevate soil pH rendering metals less-bioavailable for plant uptake. Zn fertilization, use of organic amendments, crop rotation and water management are among the other techniques successfully employed in reducing metal uptake by crop plants. However, irrespectively the mitigating measure used, heterogeneous accumulation of metals in different crop species is often reported. The inconsistency might be attributed to the genetic makeup of the crops for selective uptake, their morphological characteristics, position of edible parts on the plants in respect of their distance from roots, crop management practices, the season and to the soil characteristics. However, a sound conclusion in this regard can only be made when more scientific evidence is available on case-specific researches, in particular from long-term field trials which included risks and benefits analysis also for various remediation practices.

• Korean Journal of Organic Agriculture
• /
• v.7 no.2
• /
• pp.125-151
• /
• 1999

After the release of facts that the high nitrate contents in vegetables by Korean organic farming, organic farmers were recommended by Korean Organic Farmer Association to apply 20t/ha compost while they applied before as much as they could, sometimes even more than 100t/ha. This study was aimed to check the safety of Korean organic product in terms of nitrate content. Current nitrate content in leaf and root vegetables by 3 different farming systems(organic farming, conventional farming, greenhouse farming) were monitored and furthermore it was compared with previously published another data in Korea to find out any changes among the monitored years(1993-1999). Current nitrate content in chinese cabbage, lettuce and kale became less compare to those of the beginning of monitoring, and especially those cultivated organic farming got the lowest value while previous organic vegetables at beginning of 90's showed the higher value than those cultivated in greenhouse. This decrease in organic vegetables was affected by less application rate of organic fertilizer than before at 20t/ha. But the nitrate level by organic farming was still higher compare to those cultivated by conventional farming in open field, since currently monitored organic vegetables were cultivated basically in greenhouse condition. It shows the organic farmer the necessity of transfer their farming site and condition from greenhouse to open field in order to decrease of its high level of nitrate caused long-term application and slow release characteristics of organic fertilizer. It was concluded the adoption of soil nitrate test to recommend a organic farmer the exact application rate for need of crop growth. Additionally the mechanism of lower nitrate accumulation in rice and fruit vegetables were also discussed in the paper.

• Smart Media Journal
• /
• v.7 no.3
• /
• pp.51-56
• /
• 2018

Banana is the eighth most important crop in the world designated by the United Nations Food and Agriculture Organization (FAO). In terms of production, it is the fourth most harvested crop following wheat, rice, and corn, considered to be a promising food source for mankind as it is not only scrumptious but also rich in nutrients. However, abnormal cultivation methods that mankind has invented to breed bananas is currently pushing them to the state of extinction. The aim of this study is to develop information-rich digital contents that can easily and intriguingly convey information about steadily but certainly increasing risk of banana extinction. The end-users are middle and high school students who are assumed to be aware of the agricultural revolution through their school curriculum. The linear storytelling method was meant to encourage the end-users to be interested in the causes and processes in which banana has become endangered. For generating a natural interaction between the content and the end-users, a parallel, upper-lower structure was used, in which the relationship between the stories comprising several stages and the information graphic supporting each story is represented. This paper can support an information campaign about the endangered species.

• Smart Structures and Systems
• /
• v.6 no.5_6
• /
• pp.439-459
• /
• 2010

Structural health monitoring (SHM) of civil infrastructure using wireless smart sensor networks (WSSNs) has received significant public attention in recent years. The benefits of WSSNs are that they are low-cost, easy to install, and provide effective data management via on-board computation. This paper reports on the deployment and evaluation of a state-of-the-art WSSN on the new Jindo Bridge, a cable-stayed bridge in South Korea with a 344-m main span and two 70-m side spans. The central components of the WSSN deployment are the Imote2 smart sensor platforms, a custom-designed multimetric sensor boards, base stations, and software provided by the Illinois Structural Health Monitoring Project (ISHMP) Services Toolsuite. In total, 70 sensor nodes and two base stations have been deployed to monitor the bridge using an autonomous SHM application with excessive wind and vibration triggering the system to initiate monitoring. Additionally, the performance of the system is evaluated in terms of hardware durability, software stability, power consumption and energy harvesting capabilities. The Jindo Bridge SHM system constitutes the largest deployment of wireless smart sensors for civil infrastructure monitoring to date. This deployment demonstrates the strong potential of WSSNs for monitoring of large scale civil infrastructure.

• Earthquakes and Structures
• /
• v.3 no.3_4
• /
• pp.581-609
• /
• 2012

In this paper a novel non-iterative approach is proposed to address the problem of deriving non-stationary stochastic processes which are compatible in the mean sense with a given (target) response (uniform hazard) spectrum (UHS) as commonly desired in the aseismic structural design regulated by contemporary codes of practice. This is accomplished by solving a standard over-determined minimization problem in conjunction with appropriate median peak factors. These factors are determined by a plethora of reported new Monte Carlo studies which on their own possess considerable stochastic dynamics merit. In the proposed approach, generation and treatment of samples of the processes individually on a deterministic basis is not required as is the case with the various approaches found in the literature addressing the herein considered task. The applicability and usefulness of the approach is demonstrated by furnishing extensive numerical data associated with the elastic design UHS of the current European (EC8) and the Chinese (GB 50011) aseismic code provisions. Purposely, simple and thus attractive from a practical viewpoint, uniformly modulated processes assuming either the Kanai-Tajimi (K-T) or the Clough-Penzien (C-P) spectral form are employed. The Monte Carlo studies yield damping and duration dependent median peak factor spectra, given in a polynomial form, associated with the first passage problem for UHS compatible K-T and C-P uniformly modulated stochastic processes. Hopefully, the herein derived stochastic processes and median peak factor spectra can be used to facilitate the aseismic design of structures regulated by contemporary code provisions in a Monte Carlo simulation-based or stochastic dynamics-based context of analysis.

• Korean Journal of Remote Sensing
• /
• v.35 no.3
• /
• pp.389-400
• /
• 2019

Level meters are non-invasively capable of measuring the level of the medium, and a growing variety of level meters are being used in the industry in connection with safety and maintenance. The level meter can be measured according to various kinds of medium such as solid medium such as coal, flour, rice and liquid medium such as water and petroleum. In order to reduce the error depending on the medium, the measurement using the Doppler Effect can compensate the measurement error, However, the number of signal processing steps is increased, the operation speed is further increased, the hardware complexity increases, and a high cost structure is required. In this paper, we propose a method to improve the signal processing operation structure of the remote measurement level meter to reduce the amount of computation and the resource usage of the required FPGA.

• Electronics and Telecommunications Trends
• /
• v.36 no.1
• /
• pp.54-63
• /
• 2021

Since the recent COVID-19 pandemic, countries have been strengthening trade protection for their security, and the importance of securing strategic materials, such as food, is drawing attention. In addition to the cultural aspects, the global preference for food produced in Korea is increasing because of the Korean Wave. Thus, the Korean food industry can be developed into a high-value-added export food industry. Currently, Korea has a low self-sufficiency rate for foodstuffs apart from rice. Korea also suffers from problems arising from population decline, aging, rapid climate change, and various animal and plant diseases. It is necessary to develop technologies that can overcome the production structures highly dependent on the outside world of food and foster them into export-type system industries. The global agricultural industry-related technologies are actively being modified via data accumulation, e.g., environmental data, production information, and distribution and consumption information in climate and production facilities, and by actively expanding the introduction of the latest information and communication technologies such as big data and artificial intelligence. However, long-term research and investment should precede the field of living organisms. Compared to other industries, it is necessary to overcome poor production and labor environment investment efficiency in the food industry with respect to the production cost, equipment postmanagement, development tailored to the eye level of field workers, and service models suitable for production facilities of various sizes. This paper discusses the flow of domestic and international technologies that form the core issues of the site centered on the 4th Industrial Revolution in the field of agriculture, livestock, and fisheries. It also explains the environmental awareness production technologies centered on sustainable intelligence platforms that link climate change responses, optimization of energy costs, and mass production for unmanned production, distribution, and consumption using the unstructured data obtained based on detection and growth measurement data.

• Journal of Conservation Science
• /
• v.30 no.2
• /
• pp.137-148
• /
• 2014

Large scale anoxic chamber system(volume $28m^3$) was developed and installed at The National Folk Museum of Korea for the first time in Korea. In order to get optimal anoxic treatment condition, we compared the disinfection of adults, larvae and eggs of cigarette beetles using nitrogen and argon. The time for complete disinfection of cigarette beetles in pine wooden blocks exposed to nitrogen at oxygen concentration 0.01% and 50% in relative humidity were 15 days at $20^{\circ}C$, 10 days at $25^{\circ}C$, and 7 days $30^{\circ}C$. Time were 10 days at $20^{\circ}C$, 7 days at $25^{\circ}C$, and 5 days $30^{\circ}C$ in argon anoxic atmosphere. From the mortality of cigarette beetles, optimal disinfection condition was oxygen concentration 0.01%, $25^{\circ}C$ in temperature, 50% in relative humidity and exposure time 21 days at nitrogen atmosphere. And when large scale anoxic chamber system was supplied nitrogen by nitrogen generator for anoxic treatment of many collections or large collections, it could be operated stably. To verify optimal disinfection condition, museum insects(adults, larvae, pupae and eggs of cigarette beetles in pine wooden blocks, cotton fabrics and Korean paper book, adults and larvae of drugstore beetles in pine wooden blocks, cotton fabrics and Korean paper book, larvae of varied carpet beetles in pine wooden block and silk fabrics, adults and larvae of hide beetles and adults of rice weevils in breeding boxes) which exposed at optimal disinfection condition, were completely killed.

• Journal of Broadcast Engineering
• /
• v.21 no.3
• /
• pp.425-435
• /
• 2016

In this paper, we propose a classification model by analyzing raw material images recorded using a color CCD camera to automatically classify good and defective agricultural products such as rice, coffee, and green tea, and raw materials. The current classifying agricultural products mainly depends on visual selection by skilled laborers. However, classification ability may drop owing to repeated labor for a long period of time. To resolve the problems of existing human dependant commercial products, we propose a vision based automatic raw material classification combining mean shift clustering and stepwise region merging algorithm. In this paper, the image is divided into N cluster regions by applying the mean-shift clustering algorithm to the foreground map image. Second, the representative regions among the N cluster regions are selected and stepwise region-merging method is applied to integrate similar cluster regions by comparing both color and positional proximity to neighboring regions. The merged raw material objects thereby are expressed in a 2D color distribution of RG, GB, and BR. Third, a threshold is used to detect good and defective products based on color distribution ellipse for merged material objects. From the results of carrying out an experiment with diverse raw material images using the proposed method, less artificial manipulation by the user is required compared to existing clustering and commercial methods, and classification accuracy on raw materials is improved.