• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.3
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• pp.100-107
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• 2002

In this paper, we propose an expert system for electronic interlocking which enhances the safty, efficiency and expanability of the existing system by designing real-time interlocking control based on the interlocking table automatically generated using artificial intelligence approach. The expert system consists of two parts; an interlocking table generation part and a real-time interlocking control part. The former generates automatically the interlocking relationship of all possible routes by searching dynamically the station topology which is obtained from station database. On the other hand, the latter controls the status of station facilities in real-time by applying the generated interlocking relationship to the signal facilities such as signal devices, points, track circuits for a given route. The expert system is implemented in C language which is suitable to implement the interlocking table generation part using the dynamic memory allocation technique. Finally, the effectiveness of the expert system is proved by simulating for the typical station model.

• Structural Monitoring and Maintenance
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• v.1 no.2
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• pp.213-230
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• 2014

A novel real-time actuator failure detection algorithm is developed in this paper. Actuator fails when the input to the structure is different from the commanded one. Previous research has shown that one error function can be formulated for each actuator through interaction matrix method. For output without noise, non-zero values in the actuator functions indicate the instant failure of the actuator regardless the working status of other actuators. In this paper, it is further demonstrated that the actuator's error function coefficients will be directly calculated from the healthy input of the examined actuator and all outputs. Hence, the need for structural information is no longer needed. This approach is termed as direct method. Experimental results from a NASA eight bay truss show the successful application of the direct method for isolating and identifying the real-time actuator failure. Further, it is shown that the developed method can be used for real-time sensor failure detection.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2727-2729
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• 2002

In an emergency telemedicine system such as High-quality Multimedia based Real-time Emergency Telemedicine(HMRET) service, it is very important to examine the status of the patient continuously using the multimedia data including the biological signals(ECG, BP, Respiration, $SpO_2$) of the patient. In order to transmit these data real time through the communication means which have the limited transmission capacity. It is also necessary to compress the biological data besides other multimedia data. For the HMRET service, we developed the lossless biological signal compression program in MSVC++ 6.0 using DPCM method and JPEG Huffman table, and tested in an internet environment.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.249-252
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• 2008

This paper presents a new dynamically adaptable polling scheme for efficient support of real-time traffic over an IEEE 802.11 wireless LAN network. The poll scheduling plays an important role in IEEE 802.11 PCF. However, the current version of the polling list management scheme proposed in the IEEE802.11 standard is inefficient when a variable number of mobile stations have variable packets to transmit. If Point Coordinator has an exact information on the station status, it is possible to efficiently perform polling. In this thesis, we suggest an adaptable polling scheme to meet requirements of the stations. In our scheme, each station transmits packets including a piggyback information to inform that it wants to receive a poll in the next polling duration. Simulation results indicate that our scheme may reduces the packet discard ratio and real-time packet transfer delay.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.4
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• pp.45-56
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• 2022

Recently, the airport operator provides information such as real-time airport processing status, which allows users to determine the time to arrive at the airport at their own judgment. It is provided through their website and mobile Apps in order to resolve the customer's failure to board the aircraft and the inconvenience caused by waiting for the airport, etc. However, there was a lack of research cases on the intention of users to continue using such real-time airport information. Therefore, research on the field was studied by applying flow and trust theory based on human emotions. The research method verified reliability, validity, correlation between variables, and hypotheses using structural equations. As a result of the study, it was found that flow and trust had a significant effect on the intention to continue using. In other words, passengers were intended to continue to use the behavior they were searching for when they felt wise, enjoyable, and reliable etc.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.99-108
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• 2021

Digital twins are digital replicas of objects and systems in the real world. These digital replicas in a virtual environment can be connected with smart sensors and a variety of analyses, and simulations of real-time data from these sensors enable effective the operation, rapid feedback, and future predictions of real world phenomena. Until now, digital twins have been adopted and used mainly in the field of manufacturing, especially for smart factories. As digital twins are expected to be useful not only for productivity improvement but also for social problem solving, it is predicted that they will be extended to other fields such as those of transportation and cities. Digital twins will especially help realize smart cities through real-time monitoring, operation, and predictions using virtual digital twin cities. This paper summarizes the trends in digital twins for smart cities, the concept of digital twins, their application to smart cities, the strategies of various countries, and the development status of companies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.239-244
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• 2013

A ubiquitous-based construction site management system coupled with construction processing status of a 3-D spatial information and sensor network for construction site management is implemented. The service of such management system is able to save efforts and times to check the processing status of construction sites and more the related construction staff in charge can receive the real time information of construction field or the related information can be transmitted to the office where the construction staffs in charge are. Especially we can provide on a mobile smart phone of real time processing status at construction field and environmental information of such temperature, humidity, information of GPS, etc. which are able to affect the construction status. In addition, construction processing and design modification etc. as well as necessary informations are able to be helped and provided at any time and to any place.

• Spatial Information Research
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• v.22 no.4
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• pp.67-76
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• 2014

Recently, through the development of IT and mobile technology, spatial information plays a role of infrastructure of the people life and the national economy. Many kinds of applications including SNS and social commerce is to leverage the spatial information for their services. In the case of domestic, spatial open platform that can provide national spatial data infrastructure services in a stable manner has been released. And many people have been interested to the open platform services. However, the open platform currently has many difficulties to analyze its service status and load in real time, because it does not hold a real-time monitoring system. Therefore, we propose a method that can analyze the real-time service status of the open platform using the analysis of the web server log information. In particular, we propose the results of the analysis as follows: amount of data transferred, network bandwidth, number of visitors, hit count, contents usage, and connection path. We think the results presented in this study is insufficient to understand the perfect service status of the open platform. However, it is expected to be utilized as the basic data for understanding of the service status and for system expansion of the open platform, every year.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.

• Agricultural and Biosystems Engineering
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• v.7 no.1
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• pp.18-26
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• 2006

In-field site-specific nitrogen (N) management increases crop yield, reduces N application to minimize the risk of nitrate contamination of ground water, and thus reduces farming cost. Real-time N sensing and fertilization is required for efficient N management. An 'on-the-go' site-specific N management system was developed and evaluated for the supplemental N application to com (Zea mays L.). This real-time N sensing and fertilization system monitored and assessed N fertilization needs using a vision-based spectral sensor and controlled the appropriate variable N rate according to N deficiency level estimated from spectral signature of crop canopies. Sensor inputs included ambient illumination, camera parameters, and image histogram of three spectral regions (red, green, and near-infrared). The real-time sensor-based supplemental N treatment improved crop N status and increased yield over most plots. The largest yield increase was achieved in plots with low initial N treatment combined with supplemental variable-rate application. Yield data for plots where N was applied the latest in the season resulted in a reduced impact on supplemental N. For plots with no supplemental N application, yield increased gradually with initial N treatment, but any N application more than 101 kg/ha had minimal impact on yield.