• International Journal of Contents
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• v.14 no.2
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• pp.24-29
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• 2018

In this paper, we propose an efficient traffic light detection (TLD) method as an advanced driver assistance system (ADAS) for elderly drivers. Since an increase in traffic accidents is associated with the aging population and an increase in elderly drivers causes a serious social problem, the provision of ADAS for older drivers via TLD is becoming a necessary(Ed: verify word choice: necessary?) public service. Therefore, we propose an economical TLD method that can be implemented with a simple black box (built in camera) and a smartphone in the near future. The system utilizes a color pre-processing method to differentiate between the stop and go signals. A mathematical morphology algorithm is used to further enhance the traffic light detection and a circular Hough transform is utilized to detect the traffic light correctly. From the simulation results of the computer vision and image processing based on a proposed algorithm on Matlab, we found that the proposed TLD method can detect the stop and go signals from the traffic lights not only in daytime, but also at night. In the future, it will be possible to reduce the traffic accident rate by recognizing the traffic signal and informing the elderly of how to drive by voice.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.17-23
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• 2017

A connected car's major factor is connectivity and it can be applied for new concept smart PC hardware and software design method of digital virtual assistance using voice recognition engine at server when infotainment functions are implemented because internet connecting LTE or 5G wireless mobile communication is always is possible. In this paper, a hardware architecture of smart auto-PC and software architecture based on GENIVI platform, and necessary functions are proposed. Also an effective analysis and design method of connected car infotainment system will be presented by showing user requirement analysis using object-oriented method, flowchart and screen design.

• Physical Therapy Korea
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• v.16 no.2
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• pp.16-23
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• 2009

The purpose of this study was to investigate the effects postural changes on respiratory muscles and acoustic parameters of the children with spastic cerebral palsy. Nine children with spastic cerebral palsy who required assistance when walking were selected. The ages of the children ranged from 6 to 9 years old. The phonation of the sustained vowel /a/ and the voice qualities of each child such as fundamental frequency($F_0$; Hz), pitch variation (Jitter; %), amplitude variation (Shimmer; %) and noise to harmonic ratio (NHR) were analyzed by Multi-Dimensional Voice Program (MDVP). The muscle activity of three major respiratory muscles: pectoralis major muscle, upper trapezius muscle and rectus abdorminalis muscle, were measured by examining the root mean square (RMS) of the surface EMG to investigate the impact of changes in the adjusted sitting posture of each subject. However, the RMS of pectoralis major muscle showed a significant differences (p<.05). Secondly, there were no significant differences in $F_0$, Jitter and Shimmer between pre and post posture change, but there was a significant difference in NHR (p<.05). The data were collected in each individual; once prior and once after the sitting posture change. The data were analyzed by Wilcoxon signed ranks-test using SPSS version 14.0 for Windows. The findings of this study were as follows; Firstly, the RMS of upper trapezius and rectus abdorminalis muscle were not significant different between pre and post sitting posture changes. From the result, it is concluded that changes in the adjusted sitting posture decreases the abnormal respiratory patterns in the children with spastic cerebral palsy which is characterized by the hyperactivity of the respiratory muscles in breathing. Also, there is increased on the voice qualities in children with spastic cerebral palsy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.903-906
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• 1993

Lipreading through visual processing techniques help provide some useful systems for the hearing impaired to learn communication assistance. This paper proposes a method to understand spoken words by using visual images taken by a camera with a video-digitizer. The image is processed to obtain the contours of lip, which is approximated into a hexagon. The pattern lists, consisting of lengths and angles of hexagon, are compared and computed to get the fuzzy similarity between two lists. By similarity matching, the mouth shape is recognized as the one which has the pronounced voice. Some experiments, exemplified by recognition of the Japanese vowels, are given to show feasibilities of this method.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.202-209
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• 2003

We succeeded to build a cost effective assistance robotic arm with a compact and lightweight body. The robotic arm has three joints, and the tip of robotic arm to install tools consists of a closed link mechanism, which consisted of two actuators and several links. The robotic arm has been made possible by the use of actuators typically used in radio control devices. The controller of the robotic arm consists of a single chip PIC only. The robotic arm has a friendly user interface, as the operators are aged and disabled in most cases. The operator can manipulate the robotic arm by voice commands or by pressing a push button. The robotic arm has been successfully prototyped and tested on an elderly patient to assist with eating. The results of field test were satisfactory.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.287-310
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• 2022

Companies' interest in developing AI-based intelligent new products is increasing. Recently, the main concern of companies is to innovate customer experience and create new values by developing new products through the effective use of Artificial intelligence technology. However, due to the nature of products based on radical technologies such as artificial intelligence, intelligent products differ from existing products and development methods, so it is clear that there is a limitation to applying the existing development methodology as it is. This study proposes a new research method based on KANO-TOPSIS for the successful development of AI-based intelligent new products by using car voice assistants as an example. Using the KANO model, select and evaluate functions that customers think are necessary for new products, and use the TOPSIS method to derives priorities by finding the importance of functions that customers need. For the analysis, major categories such as vehicle condition check and function control elements, driving-related elements, characteristics of voice assistant itself, infotainment elements, and daily life support elements were selected and customer demand attributes were subdivided. As a result of the analysis, high recognition accuracy should be considered as a top priority in the development of car voice assistants. Infotainment elements that provide customized content based on driver's biometric information and usage habits showed lower priorities than expected, while functions related to driver safety such as vehicle condition notification, driving assistance, and security, also showed as the functions that should be developed preferentially. This study is meaningful in that it presented a new product development methodology suitable for the characteristics of AI-based intelligent new products with innovative characteristics through an excellent model combining KANO and TOPSIS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.157-163
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• 2020

Recently, fine dust has been known to cause cardiovascular diseases here, raising interest in ways to reduce emissions by efficiently using fuel from cars that cause air pollution. Accordingly, a driving assistance system was developed to save fuel by eco-driving and improve the driver's bad driving habits. The system was developed using raspberry pi, arduino and Android. Using RPM, speed, fuel injection information obtained from OBD-II, and gyro-sensor values, Fuel-Cut is induced to create an optimal inertial driving environment. It also provides various information system such as weather, driving environment, and preventing drowsy driving through GUI and voice recognition functions. It is possible to check driving records and vehicle fault information using Android application and has low overhead for message transmission using MQTT protocol optimized for IoT environment.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.78-86
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• 2017

The Internet of Things can offer disabled people the assistance and support, which is essential to achieve a good quality of life. The visually impaired people need assistance in finding locations, detecting obstacles on the way, and getting directions while moving around to reach their destination. Based on this persistent need, this paper proposes a navigation system for blind people using Internet of Things. The technologies used in our proposed system are: a smart cane containing an RFID reader and an ultrasonic sensor, a smart phone and Internet. The sensed data from the ultrasonic sensor for detecting obstacle is converted to International Standard format from ISO/IEC 23005-5 (MPEG-V Part 5). The system detects the blind person's location using the RFID tags implemented on the way. The system uses voice message in the smart phone to communicate with the blind person to lead him to his destination. The proposed system has been tested to navigate successfully in the campus.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.372-375
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• 2008

Drivers need to process dynamic stimulus in real - time with full attention from Telematics environment. However, as the information technology revolution brings more and more data into vehicles, all of it competing for the drivers' attention, the development of automated assistance for driver information processing becomes increasingly import ant. There for e, drivers' workload is very essential factor for safety driving in Telematics environment. In this paper, we have discussed driver distraction caused by driver conversation while driving and proposed voice activity detection algorithm for measuring driver workload. Finally, we show how voice activity detection system works for measuring driver workload.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.1001-1010
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• 2021

Normal people are not deeply aware of their dependence on sight when eating. However, since the visually impaired do not know what kind of food is on the table, the assistant next to them holds the blind spoon and explains the position of the food in a clockwise direction, front and rear, left and right, etc. In this paper, we describe the development of a meal assistance system that recognizes each food image and announces the name of the food by voice when a visually impaired person looks at their table using a smartphone camera. This system extracts the food on which the spoon is placed through the YOLO model that has learned the image of food and tableware (spoon), recognizes what the food is, and notifies it by voice. Through this system, it is expected that the visually impaired will be able to eat without the help of a meal assistant, thereby increasing their self-reliance and satisfaction.