• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.5
• /
• pp.1071-1076
• /
• 2012

As interest about safety of agricultural products has increased, attempts to establish food safety also have been actively made. One example is GAP(Good Agricultural Practices) information service. This service supplies the safe agricultural products to consumers by establishing the safety management system from their production to sale of the agricultural products. In this parer, the proposed system enables the users to easily use it by providing GAP information service and using RFID.

• 한국데이터정보과학회:학술대회논문집
• /
• 2006.04a
• /
• pp.213-219
• /
• 2006

Considering all the factors involved in beef production individual identification using DNA marker testing is the most appropriate solution to give all the breeders' information to the consumers. After taking into account the genealogical information from the Hanwoo, only animals that did not share some parent or grandparent were analysed 33 from the 305 initially sampled. Ten major microsatellite markers were selected from allele amplified and their frequencies, H(Heterozygosity) and PIC(Polymorphism information content) with Hardy-Weinberg equilibrium. Next, in order to evaluate the power of the markers selected on the individual animal identification, the match probability(MP) and the relatedness coefficient(R) were computed.

• Agribusiness and Information Management
• /
• v.1 no.2
• /
• pp.23-42
• /
• 2009

As technology develops, more advanced technologies involving GPS, GIS, RFID and sensor networks have been adopted in agriculture sector for u-Farm. However, technology adoptions have been evaluated as ineffective. Farmers and agri-business have low level of understanding on technology so it is not efficiently utilized. This study introduces a case of RFID/sensor networks of mushroom farm as a u-Farm case study, focusing on developing a framework for analysis of u-Farm investment returns. RFID and sensor networks improve real-time production control, processing management, and traceability. Integration of RFID and sensor networks leads to innovation into the mushroom farm, reducing labor cost, increasing productivity, and improving quality of the mushroom. The ROI which is used as an indicator of performance indicator is 413%.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2008.06a
• /
• pp.291-295
• /
• 2008

오늘날 정보기술(IT)은 다양한 산업분야 융화되어 기존 산업의 경쟁력을 강화하고 생산성 및 품질 향상의 견인차 역할을 수행하고 있다. 특히 생산 및 물류 분야에서 IT 융합을 통한 새로운 시너지 창출을 시도하고 있는 것이 RFID 기술이라 할 수 있다. 이미 정부 주도의 시범사업이 끝났으며, 2008년 공공기간 확산사업이 성공적으로 마무리되면, 본격적으로 산업분야 확산이 기대되고 있다. 본 논문에서 자동차 산업에서의 RFID 응용 모델로서 RFID 기반 지능형 직서열 생산시스템의 설계 및 구현에 대하여 기술한다. 직서열 시스템은 완성차 생산라인의 조립시간과 순서에 맞춰 모듈과 부품을 공급하는 협업 생산시스템이다. 자동차 조달물류 프로세스 혁신을 위하여 RFID 기술을 도입함으로써 협력기업간 정보 교환을 원활하게 지원하며 실시간 추적관리 체제의 구현을 이루고자 한다. 본 논문에서 제안하는 시스템은실시간 재고 파악 및 생산물량 예측이 가능하며, 이기종 부품 장착에 의한 조립불량률을 현저히 줄일 수 있는 장점이 있다.

• The Korean Journal of Community Living Science
• /
• v.17 no.3
• /
• pp.55-65
• /
• 2006

Recent trends of global food production, processing, distribution and preparation under free trade circumstance are creating an increase in common' concerns about food safety. It is important that farmers improve agricultural products/food safety for satisfying consumer needs and health. Cognizant to the situation, this study was conducted to analyze how the Producers gather information, and determine their awareness about agricultural Products safety using a safety Questionnaire. The Questionnaire was given to 500 farmers who cultivate rice, fruit trees, vegetables, and other crops from September through October 2005. More than half of the producers felt concerns about the agricultural products/foods safety. Uneasiness of the producers was higher amongst those who were younger and earned a higher income. Pesticides and zoonosis (BSE AI, etc.) emerged as the main risk factors causing concerns among the greatest number of producers. Producers had a positive opinion of the effects and perception of food safety, but no opinion of the activity of government. The producers showed a high level of understanding of the Country of Origin Labeling System (88.2%), the quality certification system of agricultural and livestock products (71.9%), and the raising system of environment-friendly agriculture (72.7%). However, their level of understanding of the GAP (59.3%) and the Traceability System (22.8%) was still low. To effectively implement these policies, awareness of producers who are the beneficiaries of the above policies has to be enhanced. Therefore, the safety information should be provided at a more appropriate time and should be easier to understand.

• Animal Bioscience
• /
• v.36 no.6
• /
• pp.980-989
• /
• 2023

Objective: Iris pattern recognition system is well developed and practiced in human, however, there is a scarcity of information on application of iris recognition system in animals at the field conditions where the major challenge is to capture a high-quality iris image from a constantly moving non-cooperative animal even when restrained properly. The aim of the study was to validate and identify Black Bengal goat biometrically to improve animal management in its traceability system. Methods: Forty-nine healthy, disease free, 3 months±6 days old female Black Bengal goats were randomly selected at the farmer's field. Eye images were captured from the left eye of an individual goat at 3, 6, 9, and 12 months of age using a specialized camera made for human iris scanning. iGoat software was used for matching the same individual goats at 3, 6, 9, and 12 months of ages. Resnet152V2 deep learning algorithm was further applied on same image sets to predict matching percentages using only captured eye images without extracting their iris features. Results: The matching threshold computed within and between goats was 55%. The accuracies of template matching of goats at 3, 6, 9, and 12 months of ages were recorded as 81.63%, 90.24%, 44.44%, and 16.66%, respectively. As the accuracies of matching the goats at 9 and 12 months of ages were low and below the minimum threshold matching percentage, this process of iris pattern matching was not acceptable. The validation accuracies of resnet152V2 deep learning model were found 82.49%, 92.68%, 77.17%, and 87.76% for identification of goat at 3, 6, 9, and 12 months of ages, respectively after training the model. Conclusion: This study strongly supported that deep learning method using eye images could be used as a signature for biometric identification of an individual goat.

• Asian-Australasian Journal of Animal Sciences
• /
• v.27 no.7
• /
• pp.926-931
• /
• 2014

Pork from Jeju black pig (population J) and Berkshire (population B) has a unique market share in Korea because of their high meat quality. Due to the high demand of this pork, traceability of the pork to its origin is becoming an important part of the consumer demand. To examine the feasibility of such a system, we aim to provide basic genetic information of the two black pig populations and assess the possibility of genetically distinguishing between the two breeds. Muscle samples were collected from slaughter houses in Jeju Island and Namwon, Chonbuk province, Korea, for populations J and B, respectively. In total 800 Jeju black pigs and 351 Berkshires were genotyped at thirteen microsatellite (MS) markers. Analyses on the genetic diversity of the two populations were carried out in the programs MS toolkit and FSTAT. The population structure of the two breeds was determined by a Bayesian clustering method implemented in structure and by a phylogenetic analysis in Phylip. Population J exhibited higher mean number of alleles, expected heterozygosity and observed heterozygosity value, and polymorphism information content, compared to population B. The $F_{IS}$ values of population J and population B were 0.03 and -0.005, respectively, indicating that little or no inbreeding has occurred. In addition, genetic structure analysis revealed the possibility of gene flow from population B to population J. The expected probability of identify value of the 13 MS markers was $9.87{\times}10^{-14}$ in population J, $3.17{\times}10^{-9}$ in population B, and $1.03{\times}10^{-12}$ in the two populations. The results of this study are useful in distinguishing between the two black pig breeds and can be used as a foundation for further development of DNA markers.

• Korean Journal of Construction Engineering and Management
• /
• v.20 no.1
• /
• pp.114-123
• /
• 2019

Tracking ICT applications on construction business processes is critical to the success of ICT-applied construction projects. Existing IDEF0 is a representative modeling method for visualizing and analyzing business processes. It defines a construction production process into a visual information model, hence, encouraging the project participant to understand the activities, their deliverable, and control flow of the process. However, IDEF0 dose not lend itself to ICT-applied construction processes, because it does not provide a mean to define how, in what order, by which each and every activity that ICT applied implements. This paper presents a new business modeling method that improves the traceability of ICT application (IAMB: ICT Application tracking Model for Business process) for construction management. The IAMB contributes to handle the sophisticated features of construction management processes to which ICT are applied. The method categorizes the process into three types: management, construction, and information exchange. The validity of IAMB was confirmed by analyzing the performance when it is used for tracking each modeling step of lift reservation process which making use of ICT. The test case provides an admissible evidence that the method encourage to define who, what, how, which order, and by which ICT tools the construction process exchanges production information.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.12 no.1
• /
• pp.1-12
• /
• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.42 no.3
• /
• pp.80-88
• /
• 2019

Recently, automobile manufacturing companies, which are major customers of them, are requiring IATF 16949 (ISO/TS 16949) certification as a mandatory requirement to secure product quality. In particular, IATF 16949 : 2016, revised in October 2016, was reinforced product traceability requirements for production information management by lot in the production process. Therefore, small and medium-sized precision parts processing companies in the automobile industry are very difficult to survive due to quality and price competition for customers satisfaction. MES (Manufacturing Execution System) is required to solve this problem. However, small and medium sized precision parts processing enterprises are reluctant to introduce the MES which is not suitable for the manufacturing environment of them such as high cost and low utilization. Even if the system is introduced, it is difficult to operate and maintain the system because the lack of computer manpower. In this paper, we propose a method for building a lot tracking system for small and medium precision parts processing companies by reviewing relevant literature and analyzing cases. In addition, by managing the production history for each lot of the final product in the system, we will grasp the effect of reducing the quality failure cost obtained by minimizing the range of defect selection.