• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.80-92
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• 2023

As cities are becoming densely populated, previously unexpected events such as crimes, accidents, and infectious diseases are bound to affect user demands. With a time-series prediction of demand using information with uncertainty, it is impossible to derive reliable results. In particular, the COVID-19 outbreak in early 2020 caused changes in abnormal travel patterns and made it difficult to predict demand for time series. A methodology that accurately predicts demand by detecting and reflecting these changes is, therefore, required. The current study suggests a time series modeling pipeline that automatically detects and predicts abnormal events caused by COVID-19. We expect its wide application in various situations where there is a change in demand due to irregular and abnormal events.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.17-31
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• 2023

An activity-based model requires detailed population information to model individual travel behavior in a disaggregated manner. The recent innovative approach developed deep generative models with novel regularization terms that improves fidelity and diversity for population synthesis. Since the method relies on measuring the distance between distribution boundaries of the sample data and the generated sample, it is crucial to obtain well-defined continuous representation from the discretized dataset. Therefore, we propose an improved entity embedding models to enhance the performance of the regularization terms, which indirectly supports the synthesis in terms of feasible and diverse populations. Our results show a 28.87% improvement in the F1 score compared to the baseline method.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.147-157
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• 2010

With the immergence of the iPhone, the interest in Smartphones is getting higher as services can be provided directly between service providers and consumers without the network operators. As the number of international tourists increase, individual tourists are also increasing. According to the WTO's (World Tourism Organization) prediction, the number of international tourists will be 1.56 billion in 2020,and the average growth rate will be 4.1% a year. Chinese tourists, in particular, are increasing rapidly and about 100 million will travel the world in 2020. In 2009, about 7.8 million foreign tourists visited Korea and the Ministry of Culture, Sports and Tourism is trying to attract 12 million foreign tourists in 2014. A research institute carried out a survey targeting foreign tourists and the survey results showed that they felt uncomfortable with communication (about 55.8%) and directional signs (about 21.4%) when they traveled in Korea. To solve this inconvenience for foreign tourists, multilingual servicesfor traffic signs, tour information, shopping information and so forth should be enhanced. The appearance of the Smartphone comes just in time to provide a new service to address these inconveniences. Smartphones are especially useful because every Smartphone has GPS (Global Positioning System) that can provide users' location to the system, making it possible to provide location-based services. For improvement of tourists' convenience, Seoul Metropolitan Government hasinitiated the u-tour service using Kiosks and Smartphones, and several Province Governments have started the u-tourpia project using RFID (Radio Frequency IDentification) and an exclusive device. Even though the u-tour or u-tourpia service used the Smartphone and RFID, the tourist should know the location of the Kiosks and have previous information. So, this service did not give the solution yet. In this paper, I developed a new convenient service which can provide location based information for the individual tourists using GPS, WiFi, and 3G. The service was tested at Insa-dong in Seoul, and the service can provide tour information around the tourist using a push service without user selection. This self-tour service is designed for providing a travel guide service for foreign travelers from the airport to their destination and information about tourist attractions. The system reduced information traffic by constraining receipt of information to tourist themes and locations within a 20m or 40m radius of the device. In this case, service providers can provide targeted, just-in-time services to special customers by sending desired information. For evaluating the implemented system, the contents of 40 gift shops and traditional restaurants in Insa-dong are stored in the CMS (Content Management System). The service program shows a map displaying the current location of the tourist and displays a circle which shows the range to get the tourist information. If there is information for the tourist within range, the information viewer is activated. If there is only a single resultto display, the information viewer pops up directly, and if there are several results, the viewer shows a list of the contents and the user can choose content manually. As aresult, the proposed system can provide location-based tourist information to tourists without previous knowledge of the area. Currently, the GPS has a margin of error (about 10~20m) and this leads the location and information errors. However, because our Government is planning to provide DGPS (Differential GPS) information by DMB (Digital Multimedia Broadcasting) this error will be reduced to within 1m.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.189-196
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• 2017

BIS(Bus Information System) provides the different information related to buses including predictions of arriving times at stations. BIS have been deployed almost all cities in our country and played active roles to improve the convenience of public transportation systems. Moving average filters, Kalman filter and regression models have been representative in forecasting the arriving times of buses in current BIS. The accuracy in prediction of arriving times depends largely on the forecasting algorithms and traffic conditions considered when forecasting in BIS. In present BIS, the simple prediction algorithms are used only considering the passage times and distances between stations. The forecasting of arrivals, however, have been influenced by the traffic conditions such as traffic signals, traffic accidents and pedestrians ets., and missing data. To improve the accuracy of bus arriving estimates, there are big troubles in building models including the above problems. Hidden Markov Models have been effective algorithms considering various restrictions above. So, we have built the HMM forecasting models for bus arriving times in the current BIS. When building models, the data collected from Sunchean City at 2015 have been utilized. There are about 2298 stations and 217 routes in Suncheon city. The models are developed differently week days and weekend. And then the models are conformed with the data from different districts and times. We find that our HMM models can provide more accurate forecasting than other existing methods like moving average filters, Kalmam filters, or regression models. In this paper, we propose Hidden Markov Model to obtain more precise and accurate model better than Moving Average Filter, Kalman Filter and regression model. With the help of Hidden Markov Model, two different sections were used to find the pattern and verified using Bootstrap process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.1-9
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• 2009

Bus information system(BIS), as a part of the intelligent transportation system(ITS), is one of the most advanced public transportation systems which provide the real-time bus traffic information for the users waiting the buses at the bus stop. However, correct bus information data, such as the present bus location, the user waiting time, the bus arrival time, etc. are not provided for the bus users because the proper bus arrival time predictive models are not used yet in most of the cities operating the bus information system, including the metropolitan City of Ulsan. Thus, the purpose in this study is to investigate real-time bus traffic characteristic data for identifying the bus operation characteristics on the arterial under the study in the metropolitan City of Ulsan, analyze real-time bus traffic characteristic data on the ID locations of the arterial under the study, construct the optimal unit segment models for the unit segments which are the bus stop, node and travel section using the exponential smoothing, weighted smoothing and Kalman Filter methods, respectively, and finally suggest the optimal integrated model for predicting the real-time bus arrival time at the bus stop of the arterial under the study.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.4
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• pp.441-447
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• 2000

In this paper, we design and implement an Internet GIS based on ObjectWeb, which makes to use various distributed services and object paradigm. We use CORBA, which is the standard of distributed object middleware and supports interoperability and reusability regardless of the execution environment and the implementation language of a distributed code, so that it easily extends established systems in networking environment and accesses distributed heterogeneous spatial data. Our method distributes parts of user interactive tasks to clients to reduce and to improve the system performance while existing approaches concentrate all workloads on a server. We implement a travel information system on the developed IGIS. Users receive services from remote servers employing a Java client system running on a web browser.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5168-5181
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• 2017

The popularity of augmented reality (AR) applications and games are in high demand. Currently, the best common platform to implement AR services is on a smartphone, as online games, navigators, personal assistants, travel guides are among the most popular applications of smartphones. However, the power consumption of an AR application is extremely high, and therefore, highly adaptable and dynamic low power control schemes must be used. Dynamic voltage and frequency scaling (DVFS) schemes are widely used in smartphones to minimize the energy consumption by controlling the device's operational frequency and voltage. DVFS schemes can sometimes lead to longer response times, which can result in a significant problem for AR applications. In this paper, an AR response time monitor is used to observe the time interval between the AR image input and device's reaction time, in order to enable improved operational frequency and AR application process priority control. Based on the proposed response time monitor and the characteristics of the Linux kernel's completely fair scheduler (CFS) (which is the default scheduler of Android based smartphones), a response time step control (RSC) scheme is proposed which adaptively adjusts the CPU frequency and interactive application's priority. The experimental results show that RSC can reduce the energy consumption up to 10.41% compared to the ondemand governor while reliably satisfying the response time performance limit of interactive applications on a smartphone.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.55-67
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• 2002

구간검지체계를 기반으로 한 첨단교통정보제공시스템(Advanced Traveler Information Systems)은 그 기능 수행시 다음의 중요 고려사항을 지닌다. 첫째는 제공 정보의 신뢰성이며, 둘째는 정보수집비용에 관련한 수집자료수의 한계이다. 본 논문에서는 이러한 한계성 극복을 위해 보다 대표성 있는 교통정보 형태의 설정 및 통계적으로 신뢰성 있는 정보산출을 위해 요구되는 적정표본수의 결정에 대한 연구를 수행하였다. 도시고속도로(올림픽대로)와 도시간선도로(천호대로)의 실측 구간통행시간분포 분석결과 단일교차로 구간의 경우 다른 구간들의 단일봉(unimodal)의 정규분포형태와는 다른 두 개의 봉우리를 지닌 분포형태(bimodal)가 나타났다. 따라서 이러한 구간은 기존과는 다른 새로운 교통정보 형태가 필요하며, 본 논문에서는 모든 통과차량들의 평균통행시간으로 정의되는 한 개의 대표치가 아닌 신호주기에 의한 정지여부에 따라 분리되는 주행시간과 지체시간 또는 주행속도와 통행속도 개념의 세분화된 정보형태를 설정하였다. 또한 중심극한정리를 기초로 한 통계적인 표본수 결정식을 이용하여 설정된 신뢰수준 하에서의 정보산출을 위해 요구되는 적정 표본수를 산출하였다. 그 결과, 교통이 혼잡할수록 요구되는 표본수는 적어지는 것으로 나타났다. 우선 적정 표본수 만큼의 표본추출을 하고 제안된 정보산출 방법에 의해 교통정보를 산출한 후 실측치와의 오차를 비교하였다. 그 결과 산출된 교통정보는 신뢰수준 95%와 허용오차 5㎞/h를 만족하였다. 다음으로 구간검지체계를 이용하여 정보를 산출하는 타시스템 교통정보와의 오차율을 비교하였다. 그 결과, 실측치와 본 연구의 산출방법에 의한 교통정보, 로티스교통정보 및 차량번호판 인식시스템의 교통정보와의 비교 결과 제안된 교통정보형태의 타당성을 볼 수 있었다.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.509-523
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• 2015

With the introduction of smart devices as a new channel of information distribution, the mass tourism that has been dominating the travel scene is being transformed into individual tourism. Therefore, it is more than important to establish an advanced smart tourism environment using cutting-edge ICT technologies in order to go into one of tourism developed countries. In line with that, this study draws both local and international cases to show where smart tourism stands now by mapping out problems and solutions by category. Firstly, in terms of infrastructure, establishing distribution platform and big data analyzing systems were suggested. Secondly, to fit the needs of consumers, converged tourism content and user experience based content development are in need. Lastly, in terms of governance forming public-private consultative body and incubating creative tourism companies are suggested. The study results will serve as a fruitful reference to those who want to establish business strategy related to smart tourism.