• Journal of Information Processing Systems
• /
• v.13 no.4
• /
• pp.951-969
• /
• 2017

In this paper, we newly propose a traffic information service model that collects traffic information sensed by an individual vehicle in real time by using a smart device, and which enables drivers to share traffic information on all roads in real time using an application installed on a smart device. In particular, when the driver requests traffic information for a specific area, the proposed driver-personalized service model provides him/her with traffic information on the driving directions in advance by predicting the driving directions of the vehicle based on the learning of the driving records of each driver. To do this, we propose a traffic information management model to process and manage in real time a large amount of online-generated traffic information and traffic information requests generated by each vehicle. We also propose a road node-based indexing technique to efficiently store and manage location-based traffic information provided by each vehicle. Finally, we propose a driving learning and prediction model based on the hidden Markov model to predict the driving directions of each driver based on the driver's driving records. We analyze the traffic information processing performance of the proposed model and the accuracy of the driving prediction model using traffic information collected from actual driving vehicles for the entire area of Seoul, as well as driving records and experimental data.

• Journal of KIISE:Information Networking
• /
• v.31 no.5
• /
• pp.460-468
• /
• 2004

Quality of Service (QoS)-constrained policy has an advantage to guarantee QoS requirements requested by users. Quorum systems can ensure the consistency and availability of replicated data despite the benign failure of data repositories. We propose a Quorum based resource management scheme, which includes a system resource and network resource, both of which can satisfy the requirements of application QoS. We also propose the resource reconfiguration algorithm based on temporal execution time estimation method. Resource reconfiguration means that reshuffling the current available resource set for maintaining the quality level of the resources. We evaluate the effectiveness of resource reconfiguration mechanism with a Heart Hemodynamics analysis. Our approach shows the increase of the stability of execution environment as well as decrease the completion time compare to the method that is not adapted the resource reconfiguration.

• Journal of Positioning, Navigation, and Timing
• /
• v.9 no.3
• /
• pp.175-182
• /
• 2020

This paper introduces a study to estimate the user altitude in need of rescue in an emergency. The altitude is estimated by using the barometric pressure sensor embedded in the smartphone. Compared to GPS, which is degraded in urban or indoor environments, it has the advantage of not having spatial restrictions. With the endless development of smartphone hardware, it is possible to estimate the absolute altitude using the measured value if only the bias of the embedded barometric pressure sensor is applied. The altitude information of the person in need of rescue in an emergency is a great help in reducing rescue time. Since time is tight, we propose online calibration that provides the barometric pressure sensor bias used for altitude estimation through database. Furthermore, experiments were conducted to understand the characteristics of the barometric pressure sensor, which is greatly affected by wind. At the end, the altitude estimation performance was confirmed through an actual field tests in various floors in the building.

• Smart Structures and Systems
• /
• v.26 no.6
• /
• pp.735-751
• /
• 2020

Identification of structure parameters is crucial in Structural Health Monitoring (SHM) context for activities such as model validation, damage assessment and signal processing of structure response. In this paper, guided waves generated by piezoelectric transducers are used for in-situ and non-destructive structural parameter estimation based on Bayesian approach. As Bayesian approach needs iterative process, which is computationally expensive, this paper proposes a method in which an analytical model is selected and developed in order to decrease computational time and complexity of modeling. An experimental set-up is implemented to estimate three target elastic and geometrical parameters: Young's modulus, Poisson ratio and thickness of aluminum and steel plates. Experimental and simulated data are combined in a Bayesian framework for parameter identification. A significant accuracy is achieved regarding estimation of target parameters with maximum error of 8, 11 and 17 percent respectively. Moreover, the limitation of analytical model concerning boundary reflections is addressed and managed experimentally. Pulse excitation is selected as it can excite the structure in a wide frequency range contrary to conventional tone burst excitation. The results show that the proposed non-destructive method can be used in service for estimation of material and geometrical properties of structure in industrial applications.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.24 no.3
• /
• pp.139-146
• /
• 2019

As the number of electric vehicles (EVs) in Jejudo Island increases, the secondary use of EV batteries is becoming increasingly mandatory not only in reducing greenhouse gas emissions but also in promoting resource conservation. For the secondary use of EV batteries, their capacity and performance at the end of automotive service should be evaluated properly. In this study, the battery state information from the on-board diagnostics or OBD2 port was acquired in real time while driving three distinct routes in Jejudo Island, and then the battery operating characteristics were assessed with the driving routes. The route with higher altitude led to higher current output, i.e., higher C-rate, which would reportedly deteriorate state of health (SOH) faster. In addition, the SOH obtained from the battery management system (BMS) of a 2017 Kia Soul EV with a mileage of 55,000 km was 100.2%, which was unexpectedly high. This finding was confirmed by the SOH estimation based on the ratio of the current integral to the change in state of charge. The SOH larger than 100% can be attributed to the rated capacity that was lower than the nominal capacity in EV application. Therefore, considering the driving environment and understanding the SOH estimation process will be beneficial and necessary in evaluating the capacity and performance of retired batteries for post-vehicle applications.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.2
• /
• pp.285-290
• /
• 2010

We investigate the outage probability in terms of QoS (quality of service) in indoor PLC network. We consider various kinds of appliances for realistic indoor PLC network. For estimation of the outage probability, we calculate the time-varying channel responses considering the loading conditions based on regular human activities and include the additive noise. We calculate the outage probability for each terminal and investigate relationship between the outage probability and the channel length, and transmit powers. Our results suggest that the outage probability is increased when the channel length becomes longer because more appliances affect the amount of reduced channel capacity and is not improved distinctly for very high and low outage threshold by increasing the transmit power. However, we can see outage probability improvement for 30% outage threshold case by increasing the transmit power.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.12 no.3
• /
• pp.493-498
• /
• 2017

Recently, traffic data is analyzed for efficiency of bus operation, D2D(: Door to Door) service, and self-driving of public transportation. However, various studies have been carried out to predict the delay time of public transportation, especially buses, but the research to date has been insufficient due to limitations of simple analysis and data acquisition. In this study, delay time estimation is performed by collecting and processing data such as day of the week, weather, and time of day based on bus operation information. The proposed method in this paper can be applied to autonomous public transport and public traffic control system by improving the accuracy by adding variables in the future.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.5D
• /
• pp.671-677
• /
• 2011

A diversity of railway network function enhancement projects such as the double tracking, electrification, and direct operation have been actively executed to improve the railway service. When the new rapid transit is provided, how many people will use it instead of other transports? How will the railway choice behavior be changed? Accordingly, in this paper, the applicability of diverted travel demand forecast methods, by Revealed Preference(RP) and Stated Preference(SP) data was reviewed for Daegu metropolitan rail rapid transit service. As the result of combining RP and SP data, including the sequential and simultaneous approach, the total travel time and travel cost parameters are of the right sign and are highly significant. The simultaneous approach is more efficient in terms of the estimation of coefficients. In particular, methods to improve validity of the Mixed RP/SP models, when RP data is used proportionally, the diverted travel demand can be easily identified by railway fare and travel time service level. Therefore, it is considered that this will practically apply even in other regions as well as Daegu metropolitan railway.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.4
• /
• pp.19-25
• /
• 2016

Engineering structures including civil infrastructures require a life-cycle cost and benefit during their service lives. The service life of a structure can be extended through appropriate inspection and maintenance actions. In general, this service life extension requires more life-cycle cost and cumulative benefit. For this reason, structure managers need to make a rational decision regarding the service life management considering both the cost and benefit simultaneously. In this paper, the probabilistic decision tool to determine the optimal service life based on cost-benefit analysis is presented. This decision tool requires an estimation of the time-dependent effective cost-benefit under uncertainty to formulate the optimization problem. The effective cost-benefit is expressed by the difference between the cumulative benefit and life-cycle cost of a deteriorating structure over time. The objective of the optimization problem is maximizing the effective cost-benefit, and the associated solutions are the optimal service life and maintenance interventions. The decision tool presented in this paper can be applied to any deteriorating engineering structure.

• Proceedings of the SAREK Conference
• /
• 2007.11a
• /
• pp.316-321
• /
• 2007

It is difficult for a superintendent or an operator of building service systems and equipment to decide the reasonable time for management of himself due to the shortage of his specialty for repair or replacement of a part of or whole equipment. But The reliable life expectancies for various building service equipment have not been prepared yet. This study shows the difference of optimal economic life and the decrease of running cost and energy consumption according to management level of the building equipment by the LCC analysis. The numerical model for building HVAC system was composed and analyses were performed for several parameters with management.