• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.959-968
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• 2022

In this paper, we intend to develop a cart with the convenience of moving objects or items that are difficult to hold by the hand of the disabled and the elderly from outdoor activities to a moving location. Using GPS module, DC motor, Bluetooth module, magnetometer sensor, and Blynk application, the smart follow cart was programmed to accurately know the owner's location while following the cart. The values of latitude and longitude of the magnetometer sensor are set so that the correct leverage value can be obtained in the lead for fine adjustment of the start and stop angles so that the user's position can be freely detected. The above motor driver L298n was connected to the motor to drive the DC motor at a fine angle. A smart follow cart was implemented that receives location signals according to the direction of the owner by turning on/off the mobile phone app as a switching role by connecting the GPS through Bluetooth wireless communication using a smartphone.

• Journal of KIISE
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• v.42 no.3
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• pp.295-306
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• 2015

MOnCa2 is a framework for building intelligent smartphone applications based on smartphone sensors and ontology reasoning. In previous studies, MOnCa determined and inferred user situations based on sensor values represented by ontology instances. When this approach is applied, recognizing user space information or objects in user surroundings is possible, whereas determining the user's physical context (travel behavior, travel destination) is impossible. In this paper, MOnCa2 is used to build recognition models for travel behavior and routes using smartphone sensors to analyze the user's physical context, infer basic context regarding the user's travel behavior and routes by adapting these models, and generate high-level context by applying ontology reasoning to the basic context for creating intelligent applications. This paper is focused on approaches that are able to recognize the user's travel behavior using smartphone accelerometers, predict personal routes and destinations using GPS signals, and infer high-level context by applying realization.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.533-538
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• 2017

In this thesis, the ambulatory aid mechanism was implemented so that blind people could be safer at risk of walking outdoors. Using ultrasonic sensors, the obstacles can be detected when the distance between the obstacle is within 50 cm of the obstacle. If the light sensor becomes less than 25 lux, the LED will automatically turn on and help the safety of the visually impaired and the security of sight of the peripheral walkers. Color recognition sensors increase the rate of recognition of yellow color by the detection distance is 1cm, it vibrated when yellow light was detected. Using GPS with 7.3 m of error range, the guardian was able to check the location of the visually impaired.

• Journal of IKEEE
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• v.14 no.3
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• pp.224-231
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• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.133-142
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• 2021

Travel pattern recognition is widely used in many aspects such as user trajectory query, user behavior prediction, interest recommendation based on user location, user privacy protection and municipal transportation planning. Because the current recognition accuracy cannot meet the application requirements, the study of travel pattern recognition is the focus of trajectory data research. With the popularization of GPS navigation technology and intelligent mobile devices, a large amount of user mobile data information can be obtained from it, and many meaningful researches can be carried out based on this information. In the current travel pattern research method, the feature extraction of trajectory is limited to the basic attributes of trajectory (speed, angle, acceleration, etc.). In this paper, permutation entropy was used as an eigenvalue of trajectory to participate in the research of trajectory classification, and also used as an attribute to measure the complexity of time series. Velocity permutation entropy and angle permutation entropy were used as characteristics of trajectory to participate in the classification of travel patterns, and the accuracy of attribute classification based on permutation entropy used in this paper reached 81.47%.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.474-477
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• 2012

현대사회는 시각장애인에 대한 복지가 부족하다. 예를 들어 유도블럭의 홰손, 지폐의 점자처리의 모호함 등 시각장애인을 위해 만들어진 복지조차 사용하기 어려운게 현실이다. 그래서 우리는 무선카메라와 Window Phone을 이용하여 상기 불편함을 해소하기 위하여 이 프로젝트를 시작하였다. Guide Line Detection은 앞을 못 보는 시각장애인에게 무선카메라에 보이는 영상에서 유도블럭을 찾아 시각장애인과의 거리를 음성으로 알려준다. Bill Recognition은 지폐를 인식하여 음성으로 알려준다. 길 안내 기능은 길을 찾아가지 못하는 시각장애인에게 특정 지점마다 길 안내정보를 등록하고, 등록된 정보는 시각장애인이 실시간으로 길 안내를 받을 수 있다. 음성인식은 기기를 사용하기 힘든 시각장애인들에 대한 접근성을 높이기 위해 WinPhone Application이 제공하는 모든 기능을 흔들기와 음성만으로 사용할 수 있도록 제공한다. 무선카메라의 화질과 Window Phone의 GPS 불규칙적인 오차 때문에 많은 시행착오가 있었지만 무선카메라는 웹 캠으로, GPS오차는 BingMap API의 GPS 가상 좌표로 대체하여 프로젝트를 마칠 수 있었다.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.1-8
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• 2018

In this paper, we implement the signboard voice guidance service for visually impaired person using virtual beacon. The new location to provide a location-based service can be added easily by using virtual beacons, which are locating by Wi-fi, GPS, and so on, instead of physical beacons, which are locating by physical devices. We provide the voice service for guiding information of the captured signboard for the visually impaired when he arrived at the location registered through the virtual beacon.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.506-513
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• 2014

In recent years, research on user's activity recognition using a smart phone has attracted a lot of attentions. A smart phone has various sensors, such as camera, GPS, accelerometer, audio, etc. In addition, smart phones are carried by many people throughout the day. Therefore, we can collect log data from smart phone sensors. The log data can be used to analyze user activities. This paper proposes an approach to inferring a user's physical activities based on the tri-axis accelerometer of smart phone. We propose recognition method for four activity which is physical activity; sitting, standing, walking, running. We have to convert accelerometer raw data so that we can extract features to categorize activities. This paper introduces a recognition method that is able to high detection accuracy for physical activity modes. Using the method, we developed an application system to recognize the user's physical activity mode in real-time. As a result, we obtained accuracy of over 80%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.257-262
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• 2008

컴퓨팅 기술의 발전에 따라 선박의 안전항해를 지원하기 위해 Radar, GPS 등 다양한 장비들이 계량, 개발되고 있으며 그들은 선박 항해에 필요한 많은 정보를 제공하고 있다. 하지만 여전히 선박 충돌사고는 끊이지 않고 있으며, 선박 대형화에 힘입어 그 피해도 커지고 있는 실정이다. 이러한 선박 충돌사고는 앞에서 언급한 선박 항해 안전 장비의 성능제약을 받는 야간이나, 해상 환경 악화 시 두드러지게 발생하고 있으며, 특히 제한적인 상황에서 인간의 눈에만 의지해서 항해를 하고 있기 때문이기도 하다. 그래서 이러한 상황에서 Vision기술을 사용하여 카메라를 활용 상대선박을 자동으로 식별하는 시스템을 제안하고자 한다. 이는 선박들이 법적으로 야간이나 각종 장비들이 제한을 받는 상황에서 근처의 다른 선박에게 상황을 전달하기 위해서 등화(불빛)와 형상물을 사용해야한다는 점에서 착안하였다. 제안 시스템을 실제 해상 환경에서 실험하기에 제한점이 많아 프로토타입을 구현하여 실험실 환경에서 실험하고 사용자 평가를 실시하였다. 즉, LED를 가상 등화로 하여 선박에 설치된 것과 동일한 색상과 동일한 위치에 배치하고 이를 카메라를 활용하여 인식 실험을 하였으며 약 90%의 인식률을 보였다. 그리고 이러한 실험화면을 활용하여 항해업무 종사자 15명을 대상으로 사용자 평가를 실시하였으며 대부분의 사람들이 제안된 체계가 해상에서 유용하다고 답변하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.327-332
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• 2017

As Internet of Things (IoT) technology advances, there is a growing demand for location-based services (LBSs) to identify users' mobility and identity. The initial LBS system was mainly used to measure position information by measuring the phase of a signal transmitted from a global positioning system (GPS) satellite or by measuring distance to a satellite by tracking the code of a carrier signal. However, the use of GPS satellites is ineffective, because it is difficult to receive satellite signals indoors. Therefore, research on wireless communications systems like ultra-wide band (UWB), radio frequency identification (RFID), and ZigBee are being actively pursued for location recognition technology that can be utilized in an indoor environment. In this paper, we propose an LBS system that includes the 2.45GHz band for chirp spread spectrum (CSS), and the 3.1-10.6GHz band and the 250-750MHz bands for UWB using the IEEE 802.15.4a standard for low power-based location recognition. As a result, we confirmed that the 2.45GHz Industrial, Scientific and Medical (ISM) band RF transceiver and the ranging function can be realized in the hardware and has 0dBm output power.