• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.285-292
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• 2016

By adding short-range wireless communication function such as Bluetooth and Wi-Fi to the last vehicle in conjunction with a smart phone, a modern automobile is becoming entertainment screen to determine a variety of information such as car location information, diagnosis information, etc. through the ECU vehicle electronic control unit. In this study, by utilizing short-range communications capability of the on-board diagnostic devices and smart phones in association with the on-board diagnostics, compatibility tests among a number of smart phone models, Bluetooth and NFC(Near Field Communication) were carried out and those results were analyzed. Furthermore, composition of on-board diagnostic device having Bluetooth and NFC interface function and the fault diagnosis function were implemented, and fault diagnosis debugging program was developed. In addition, fault diagnosis data of the vehicle via the OBD-II interface was extracted. Finally, the on-board diagnostics CAN Protocol implementation has been proposed, and the results of work was analyzed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.488-491
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• 2014

Based on a complete understanding research in Information and Communication Technologies (ICT), the Intelligent Transport Systems rapidly build up innovative applications to ensure real time attainment as well remote management of driven information, provide a huge range of services and involve many actors in automotive ecosystem. In this paper, we present an intelligent cloud computing for handling data received from traffic sensing technologies. Transportations technologies applied in ITS have played a great role in collecting data from devices deployed in vehicles and highway infrastructures utilizing broadband wireless technologies to the Cloud. In order to facilitate the interested in automotive industry to use data collected and afford services to the car's owner, a scalable acquisition, access to computing resources and offered services are the primary goal of the proposed cloud computing.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.29-38
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• 2023

Although the biosignal is the best way to represent the human condition, it is difficult to acquire the biosignal of a driver driving for detecting driver's condition. As one of the methods to overcome this limitation, this paper proposes a driving stress monitoring system based on information provided by OBD-II(on-board diagnostics version II). The driving information and EDA(Electrodermal activity) data are obtained through the OBD-II scanner and E4 wristband, respectively. EDA data is used as ground truth to distinguish whether driver is stressed or not. MLP(multi-layer perceptron) neural network is used as a model to detect driving stress and is trained using driving data for about a month. To evaluate the proposed system, we used about 1 hour of driving data and the accuracy is 92%.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.6
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• pp.99-104
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• 2005

The CARB in USA has demanded OBD functions that detect any deterioration of performance of OTS as well as a simple defect of OTS which can affect emission to meet the reinforced emission regulation. In this paper, OTS plausibility monitoring functions to meet the demand from CARB are discussed. The output from OTS is used for the diagnostics of the torque converter clutch stuck and the gear ratio synchronous error. It is possible to diagnose the abnormality of OTS function by considering the oil temperature characteristics which changes according to the driving status of vehicles. In result, the OBD regulations of the CARB can be satisfied obligating car manufacturer to detect any problems in OTS functions which can affect emissions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.607-612
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• 2015

As the amount of vehicle's diagnostics data increases, the actors in automotive ecosystem will encounter difficulties to perform a real time analysis in order to simulate or to design new services according to the data gathered from the connected cars. In this paper, we have conducted a study of a Big Data solution that expresses the essential deep analytics to process and analyze vast quantities of vehicles on board diagnostics data generated by cars. Hadoop and its ecosystems have been deployed to process a large data and delivered useful outcomes that may be used by actors in automotive ecosystem to deliver new services to car owners. As the Intelligent transport system is involved to guarantee safety, reduce rate of crash and injured in the accident due to speed, addressing big data solution based on vehicle diagnostics data is upcoming to monitor real time outcome from it and making collection of data from several connected cars, facilitating reliable processing and easier storage of data collected.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1189-1192
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• 1996

In this paper, a fault diagnosis method is proposed for self-diagnostics of PLC(Programmable Logic Controller), process controller in industrial fields, and diagnosis of its external devices such as sensors and actuators. The aim of this research is proposition of systematic method of fault diagnosis of PLC control system and development of its equipment. A PLC fault diagnosis algorithm consists of self-diagnostics given by PLC makers, Inpuot/Output tracking method by analyzing sequence PLC programs, searching method of past fault cases in database using an expert system, and diagnosis of PLC units such as CPU, DI, and DO board. Finally usability of PLC fault diagnostic system is verified by testing a MELSEC PLC.

• Journal of Sensor Science and Technology
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• v.22 no.3
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• pp.191-196
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• 2013

A particulate matter sensor fabricated by MEMS process is proposed. It is developed to accommodate Euro6 on-board diagnostics regulation for diesel automobile. In the regulation, emission of diesel particulate matter is restricted to 9 mg/km. Particulate matter sensor is designed to use induced charges by charged particulate matter. To increase sensitivity of the sensor, groove is formed on sensor surface because wider surface area generates more induced charges. Sensitivity of the sensor is measured 10.6 mV/(mg/km) and the sensor shows good linearity up to 15.7 mg/km. Also its minimum detectable range is about 0.25 mg/km. It is suitable to detect failure of a diesel particulate filter which should filter particulate matter more than 9 mg/km. For removing accumulated particulate matter on the sensor which can disturb normal operation, platinum heater is designed on the backside of the sensor. The developed sensor can sense very low amount of particulate matter from exhaust gas in real-time with good linearity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.224-227
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• 2015

Data transmission via the car driver's tethered smart phone may have a volume-dependent billing in case car driver' phone transmits data in real-time to the remote data center. The on-board diagnosis data generated are temporary stored locally to mobile remote diagnosis application on the car driver's phone, and then transmit to the data center later when car driver connects to the Internet. To increase the easiest of using the remote vehicle application without blocking other tasks to be executing on the cloud, node.js stands as a suitable candidate for handling tasks of data storage on the cloud via mobile network. We demonstrate the effectiveness of the proposed architecture by simulating a preliminary case study of an android application responsible of real time analysis by using a vehicle-to- smart phones applications interface approach that considers the smart phones to act as a remote user which passes driver inputs and delivers output from external applications. In this paper, we propose a study on development of Remote Vehicle fault diagnostic system features web server architecture based event loop approach using node.js platform, and wireless communication to handle vehicle diagnostics data to a data center.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1338-1346
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• 2007

Beyond a simple voice service, the advances in performance and resolution of mobile handsets provides us various features in the field of mobile services. Also, advances in the human-machine interface, electronics and embedded system technologies have created the foundation for a dramatic shift in the way the vehicles are diagnosed and maintained. In this paper, we will show the vehicle diagnostic system using the mobile handset based on the OBD-II (On Board Diagnostics version II) protocol. After 2005, OBD-II standard is obligatory for all vehicles selling in Korea. Our research topics are OBD-II protocol converter for the mobile handset and the vehicle diagnostics system on WIPI(Wireless Internet Platform for Interoperability) mobile platform, which is the standard mobile platform in Korea.

• Journal of Applied Reliability
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• v.8 no.2
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• pp.101-111
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• 2008

Good diagnostics improves both the safety and system unavailability of digital safety systems. The measure of a diagnostic capability is called the Coverage Factor. Because the Failure Modes, Effects and Diagnostic Analysis (FMEDA) provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a component, the FMEDA can be used as a useful tool to calculate it. Through performing FMEDA on a digital signal processor (DSP) board used in a digital safety system, it is shown that some components of the DSP board can be replaced or improved to satisfy the required diagnostic coverage. That is, the FMEDA can serve as a useful verification tool to design a diagnostic capability for the DSP board.