• Journal of Korean Society for Geospatial Information Science
• /
• v.20 no.1
• /
• pp.33-41
• /
• 2012

BIS is an arrival guidance system which is able to supply passengers with bus service condition via Kiosks at a bus stop, internet and mobile service through pinpointing bus location in real time. It is very significant to improve the quality of traffic information by quality control of GIS-based bus network so as to maintain navigational information and to implement reliable BIS. Therefore this study aims to build criteria to quantitatively evaluate data quality of the product in accordance with the process in bus network data and to suggest guideline of quality control. To achieve this, we have categorized geometric and logical errors occurring during constructing bus network database by giving a specific case study on TAGO and set up sectional guideline and procedures to examine database for systematic and coherent quality control management. Proceeding from what has been said above, the outcome of our research leads to quality guarantee for objective and reliable bus network database and is fully expected to bring benefit of providing a more accurate public transportation information and improving reliability of BIS through preventing a variety of errors in system operation in advance.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.6
• /
• pp.34-39
• /
• 2001

An adaptive multi-rate (AMR) speech coder was adopted as a standard of W-CDMA by 3GPP and ETSI. The AMR coder is based on the CELP algorithm operating at rates ranging from 12.2 kbps down to 4.75 kbps, and it is a source controlled codec according to the channel error conditions and the traffic loading. In this paper, we implement the DSP S/W of the AMR coder using OakDSPCore. The implementation is based on the CSD17C00A chip developed by C&S Technology, and it is tested using test vectors, for the AMR speech codec, provided by ETSI for the bit exact implementation. The DSP B/W requires 20.6 MIPS for the encoder and 2.7 MIPS for the decoder. Memories required by the Am coder were 21.97 kwords, 6.64 kwords and 15.1 kwords for code, data sections and data ROM, respectively. Also, actual sound input/output test using microphone and speaker demonstrates its proper real-time operation without distortions or delays.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.2
• /
• pp.263-268
• /
• 2016

A rapid increase of data amount, used in ship-to-ship transmission of safety and logistics information, ships in the inland sea have trouble transmitting real-time information transmission due to an increase in traffic load caused by data transmitted by land station and offshore ships. In this study, therefore, communication is carried out by adaptively controlling the detailed beam width based on the distribution of offshore ships in land station durable in marine environment. Then after the adaptive sector system enabling real-time communication support between ships concentrated in an inland sea and land station is applied, the performance verification is conducted based on the respective Call Blocking Rates of an omnidirectional antenna, fisted sector system, and adaptive sector system. The performance verification result shows that adaptive sector system has better performance than the fixed sector system as the density of ship, q value, increases, and that the smaller the beam width is, the better performance of adaptive sector system will be.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.9
• /
• pp.2524-2532
• /
• 1999

In this paper, we present a new buffer pool management scheme designed for video type news objects to build a cost-effective News On Demand storage server for serving users requests beyond the limitation of disk bandwidth. In a News On Demand Server where many of users request for video type news objects have to be serviced keeping their playback deadline, the maximum numbers of concurrent users are limited by the maximum disk bandwidth the server provides. With our proposed buffer cache management scheme, a requested data is checked to see whether or not it is worthy of caching by checking its average arrival interval and current disk traffic density. Subsequently, only granted news objects are permitted to get into the buffer pool, where buffer allocation is made not on the block basis but on the object basis. We evaluated the performance of our proposed caching algorithm through simulation. As a result of the simulation, we show that by using this caching scheme to support users requests for real time news data, compared with serving those requests only by disks, 30% of extra requests are served without additional cost increase.

• The KIPS Transactions:PartC
• /
• v.13C no.4 s.107
• /
• pp.471-480
• /
• 2006

Recently, multimedia communication services, such as video conferencing and voice over IP, have been rapidly spread. H.323 is an international standard that specifies the components, protocols and procedures that provide multimedia communication services of real-time audio, video, and data communications over packet networks, including IP based networks. H.323 is applied to many commercial services because it supports various network environments and has a good performance. But communication services based on H.323 may have some problem because of current network trouble or mis-implementation of H.323. The understanding of this problem is a critical issue because it improves the quality of service and is easy to service maintenance. In this paper, we implement the analysis system for H.323 protocol wihch includes H.245, H.225.0, RTP, RTCP, and so on. Tills system is able to capture, parse, and present the H.323 protocol in real-time. Through the operation test and performance evaluation, we prove that our system is a useful to analyze and understand the problems for communication services based on H.323.

• Journal of the HCI Society of Korea
• /
• v.14 no.2
• /
• pp.41-47
• /
• 2019

In this study, a smart assistive device is designed to recognize pedestrian signal and to provide audio instructions for visually impaired people in crossing streets safely. Walking alone is one of the biggest challenges to the visually impaired and it deteriorates their life quality. The proposed device has a camera attached on a pair of glasses which can detect traffic lights, recognize pedestrian signals in real-time using a machine learning algorithm on GPU board and provide audio instructions to the user. For the portability, the dimension of the device is designed to be compact and light but with sufficient battery life. The embedded processor of device is wired to the small camera which is attached on a pair of glasses. Also, on inner part of the leg of the glasses, a bone-conduction speaker is installed which can give audio instructions without blocking external sounds for safety reason. The performance of the proposed device was validated with experiments and it showed 87.0% recall and 100% precision for detecting pedestrian green light, and 94.4% recall and 97.1% precision for detecting pedestrian red light.

• Advanced Industrial SCIence
• /
• v.3 no.1
• /
• pp.23-29
• /
• 2024

In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.

• Journal of the Economic Geographical Society of Korea
• /
• v.11 no.3
• /
• pp.459-475
• /
• 2008

This study analyzes the network structure of the Metropolitan Seoul subway system by applying complex network analysis methods. For the purpose, we construct the Metropolitan Seoul subway system as a network graph, and then calculate various indices introduced in complex network analysis. Structural characteristics of Metropolitan Seoul subway network are discussed by these indices. In particular, this study determines the shortest paths between nodes based on the weighted distance (physical and time distance) as well as topological network distance, since urban travel movements are more sensitive for them. We introduce an accessibility measurement based on the shortest distance both in terms of physical distance and network distance, and then compare the spatial structure between two. Accessibility levels of the system have been getting up overall, and thus the accessibility gaps have been getting lessen between center located subway stops and remote ones during the last 10 years. Passenger traffic volumes are explored from real passenger transaction databases by utilizing data mining techniques, and mapped by GIS. Clear differences reveal between the spatial patterns of real passenger flows and accessibility. That is, passenger flows of the Metropolitan Seoul subway system are related with population distribution and land use around subway stops as well as the accessibility supported by the subway network.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.2
• /
• pp.231-238
• /
• 2023

Since there is a limit to the physically visible horizon that sensors for autonomous driving can perceive, complementary utilization of digital map data such as a Local Dynamic Map (LDM) along the probable route of an Autonomous Vehicle (AV) is proposed for safe and efficient driving. Although the amount of digital map data may be insignificant compared to the amount of information collected from the sensors of an AV, efficient management of map data is inevitable for the efficient information processing of AVs. The objective of this study is to analyze the efficiency of information use and information processing time of AV according to the expansion of the active section of LDM-based static road and traffic information. To carry out this objective, a microscopic simulator model, VISSIM and VISSIM COM, was employed, and an area of about 9 km × 13 km was selected in the Busan Metropolitan Area, which includes heterogeneous traffic flows (i.e., uninterrupted and interrupted flows) as well as various road geometries. In addition, the LDM information used in AVs refers to the real high-definition map (HDM) built on the basis of ISO 22726-1. As a result of the analysis, as the electronic horizon area increases, while short links are intensively recognized on interrupted urban roads and the sum of link lengths increases as well, the number of recognized links is relatively small on uninterrupted traffic road but the sum of link lengths is large due to a small number of long links. Therefore, this study showed that an efficient range of electronic horizon for HDM data collection, processing, and management are set as 600 m on interrupted urban roads considering the 12 links corresponding to three downstream intersections and 700 m on uninterrupted traffic road associated with the 10 km sum of link lengths, respectively.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.131-145
• /
• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.