• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.191-201
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• 2019

A fast and accurate integrated traffic object detection framework was proposed and developed, harnessing a computer-vision based deep-learning approach performing automatic object detections, a multi object tracking technology, and video pre-processing tools. The proposed method is capable of detecting traffic object such as autos, buses, trucks and vans from video recordings taken under a various kinds of external conditions such as stability of video, weather conditions, video angles, and counting the objects by tracking them on a real-time basis. By creating plausible experimental scenarios dealing with various conditions that likely affect video quality, it is discovered that the proposed method achieves outstanding performances except for the cases of rain and snow, thereby resulting in 98% ~ 100% of accuracy.

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

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.2
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• pp.116-122
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• 2007

System management application system is one of the most interesting fields in Ubiquitous Sensor Networks. It conforms to the property of Ubiquitous Sensor Networks very well, and it is the closest application for commercial use. We have two kinds of system management technology, such as the one which is accessed by web browser at anytime, anywhere and another one which is for local accessed system. In this paper, our purpose is implementation of system management application system which provides Mesh Sensor Networks topology with IP based agent platform and system management server. Furthermore we introduce the functions used for our recent implementation and propose several future issues about system management application system.

• Journal of Internet Computing and Services
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• v.8 no.2
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• pp.15-22
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• 2007

As we detect defects and eliminate them in early stages, we can make better quality software. For doing this task, we need to use a defect tracking system which con effectively track and manage defects that give severe effects on software quality. Those existing defect tracking systems have some weaknesses as we apply them to organizations that use CMMI for process improvements. Major problems of those systems are that they require the organizations to collect many types of defect data at a time without providing the proper explanation and even without the support of defect management process. The organizations at CMMI maturity level 2 and 3 have problems for analyzing those defects because there is no specific process area at CMMI maturity level 2 and 3 which directly handles defect managing activites. This paper resolves those problems by developing a defect tracking system which offers methods of managing defects. And the system provides guidelines of which defects should be gathered for each CMMI mathurity levels. The system also has functions to generate various status and statistic information on defects, and to assign defect data to the person in charge so that he or she track the defect to the closure

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.63-68
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• 2004

In this paper, we propose a method about the extraction of vehicle and tracking trajectory for moving vehicle tracking system in road. This system applied to the monitoring system of the traffic flow for ATMS(advanced traffic management system) of ITS(intelligent transport system). Also, this system can solve the problem of maintenance of loop sensor. And we detected vehicle using differential image analysis. Because of the road environment changes by real time. Therefore, the method to use background image is not suitable. And we used Kalman filter and innovation value and variable search area for vehicle tracking system. Previous method using fixed search area is sensitive to the moving trajectory and the speed of vehicle. Simulation results show that proposed method increases the possibility of traffic measurement more than fixed area traffic measurement system.

• Journal of Advanced Navigation Technology
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• v.19 no.2
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• pp.123-132
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• 2015

Among various fields of the CNS/ATM, the surveillance field which includes ADS-B system, MLAT system, and WAM system is implemented. These next generation systems provide superior performance in tracking aircrafts. However, They still have error. In this paper, filtering algorithm is proposed in order to enhance aircraft tracking performance of ADS-B, MLAT, and WAM systems. The proposed method is a Robust Interacting Multiple Model filter, called Robust IMM filter, that improves IMM filter. The Robust IMM filter can not only improves the aircraft tracking performance but also track aircraft continually using estimates calculated from the filter when data losses occur. The simulation results of the proposed aircraft tracking methods show that the filtering data provides a better performance up to an average of 19.21%.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.143-148
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• 2016

There is increasing concern about security as a need for increased safety in the information industry society. However, it does not meet the needs for safety including CCTV. Therefore, in this paper, we link the processing technology using the image information to the IPS system consisting of GPS and Beacon. It designed a conventional RFID tag attached discomfort and image tracking system is limited to complement the disadvantages identifiable area. To this end, we designed a smart device and the Internet of Things convergence system and a research to ensure the accuracy and reliability of the IPS of the access control system. Finally, by leveraging intelligent video information using a PTZ camera, and set the entrant management policies it was carried out to control the situation and control. Also, by designing the integrated video tracking system, an authentication server, visualization systems were designed to establish an efficient technique for analyzing the IPS entrant behavior patterns.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.397-408
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• 2021

The construction industry has the highest occupational accidents/injuries and has experienced the most fatalities among entire industries. Korean government installed surveillance camera systems at construction sites to reduce occupational accident rates. Construction safety managers are monitoring potential hazards at the sites through surveillance system; however, the human capability of monitoring surveillance system with their own eyes has critical issues. A long-time monitoring surveillance system causes high physical fatigue and has limitations in grasping all accidents in real-time. Therefore, this study aims to build a deep learning-based safety monitoring system that can obtain information on the recognition, location, identification of workers and heavy equipment in the construction sites by applying multiple object tracking with instance segmentation. To evaluate the system's performance, we utilized the Microsoft common objects in context and the multiple object tracking challenge metrics. These results prove that it is optimal for efficiently automating monitoring surveillance system task at construction sites.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.971-976
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• 2009

This paper demonstrates the design and development of asset management systems suitable for the universities full of very various kind of assets. Universities consists of many departments, which have a multiplicity of many experimental. It is very difficult to record and manage assets with hands. In addition, the equipments are moving freely from one lab to another inside the school, which means it is tough to find the location of the assets and so some stuffs that are given lack attention are likely to disappear. So, these things occurring frequently in the university asset management environment should be considered in the design and embodiment of the asset management system. In the proposed system, location recognition of the assets is realized based on a route tracking method, so it is possible to detect the loss of the high priced assets and entrance, export, and lending of them are controlled efficiently. The system is likely to reduce the load of a manager responsible for asset management, because configured to decrease interventions of the manager in overall asset management process. Especially, the proposed system and implementation method will be suitable for small and medium-scale asset management, path tracking, history management.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.1-8
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• 2021

This study proposes a systems engineering approach for the development of an advanced planning & scheduling (APS) system for a cosmetic case manufacturing factory. The APS system makes production plans and schedules based on the injection process, which consists of 27 plastic injection machines in parallel to control recommended inventory of products. The system uses machine operation/failure information and defective product/work-in-process tracking information to support intelligent scheduling. Furthermore, a genetic algorithm model is applied to handle the complexity of heuristic rules and machine/quality constraints in this process. As a result of the development, the recommended inventory compliance rate is improved by scheduling the 30-day production plan for 15 main products.