• Title/Summary/Keyword: Location Detection Technology

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OnBoard Vision Based Object Tracking Control Stabilization Using PID Controller

  • Mariappan, Vinayagam;Lee, Minwoo;Cho, Juphil;Cha, Jaesang
    • International Journal of Advanced Culture Technology
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    • v.4 no.4
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    • pp.81-86
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    • 2016
  • In this paper, we propose a simple and effective vision-based tracking controller design for autonomous object tracking using multicopter. The multicopter based automatic tracking system usually unstable when the object moved so the tracking process can't define the object position location exactly that means when the object moves, the system can't track object suddenly along to the direction of objects movement. The system will always looking for the object from the first point or its home position. In this paper, PID control used to improve the stability of tracking system, so that the result object tracking became more stable than before, it can be seen from error of tracking. A computer vision and control strategy is applied to detect a diverse set of moving objects on Raspberry Pi based platform and Software defined PID controller design to control Yaw, Throttle, Pitch of the multicopter in real time. Finally based series of experiment results and concluded that the PID control make the tracking system become more stable in real time.

Car Frame Extraction using Background Frame in Video (동영상에서 배경프레임을 이용한 차량 프레임 검출)

  • Nam, Seok-Woo;Oh, Hea-Seok
    • The KIPS Transactions:PartB
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    • v.10B no.6
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    • pp.705-710
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    • 2003
  • Recent years, as a rapid development of multimedia technology, video database system to retrieve video data efficiently seems to core technology in the oriented society. This thesis describes an efficient automatic frame detection and location method for content based retrieval of video. Frame extraction part is consist of incoming / outgoing car frame extraction and car number frame extraction stage. We gain star/end time of car video also car number frames. Frames are selected at fixed time interval from video and key frames are selected by color scale histogram and edge operation method. Car frame recognized can be searched by content based retrieval method.

Prediction of Fire Spread and Real-Time Evacuation System according to Spatial Characteristics (공간적 특성에 따른 화재 확산 예측 및 실시간 대피 시스템 연구)

  • Nam-Gi An;Geon-Hui Lee;Min-jeong Kim;Kyu-Ho Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.617-623
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    • 2023
  • Among the fire incidents in Korea over the past decade, building fires are the most common, and property and human casualties are the most common. However, the existing fire fighting system does not only inform the location of emergency exits and guide safe routes to help casualties evacuate smoothly. A system was proposed to help successful evacuation by distinguishing vertical and horizontal characteristics using spatial characteristics. In this study, an effective evacuation system was proposed by predicting fires using temperature detection sensors and smoke sensor values, and calculating the optimal evacuation path through the Dijkstra algorithm.

Using multi-sensor for Development of Multiple Occupants' Activities Classification Model Based on LSTM (다중센서를 활용한 LSTM 기반 재실자 행동 분류 모델 개발)

  • Jin Su Park;Chul Seung Yang;Kyung-Ho Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.1065-1071
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    • 2023
  • In this paper discuss with research developing an LSTM model for classifying the behavior of occupants within a residence. The multi-sensor consists of an IAQ (Indoor Air Quality) sensor that measures indoor air quality, a UWB radar that tracks occupancy detection and location, and a Piezo sensor to measure occupants' biometric information, and collects occupant behavior data such as going out, staying, cooking, cleaning, exercise, and sleep by constructed an experimental environment similar to the actual residential environment. After the data with removed outliers and missing, the LSTM model is used to calculate accuracy, sensitivity, specificity of the occupant behavior classification model, T1 score.

Development of Safety Sensor for Vehicle-Type Forest Machine in Forest Road

  • Ki-Duck Kim;Hyun-Seung Lee;Gyun-Hyung Kim;Boem-Soo Shin
    • Journal of Forest and Environmental Science
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    • v.39 no.4
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    • pp.254-260
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    • 2023
  • A sensor system has been developed that uses an ultrasonic sensor to detect the downhill slope on the side of a forest road and prevents a vehicle-type forest machine from rolling down a mountainside. A specular reflection of ultrasonic wave might cause severe issues in measuring distances to targets. By investigating the installation angle of the sensor to minimize the negative effects of specular reflection, the installation angle of lateral monitoring ultrasonic sensor could be determined based on the width of road shoulder. Obstacles such as small rocks or piece of log in a forest road may cause the forest machine to be overturned while the machine riding over due to excessive its posture change. It was determined that the laser sensor could be a part of a sensor system capable of specifying the location and size of small obstacles. Not only this sensor system including ultrasonic and laser sensors can issue a warning of dangerous sections to drivers in forest forwarders currently in use, but also it can be used as a driving safety sensor in autonomous forest machine or remote-control forest machine in the future.

Design of Indoor Space Guidance System Using LiDAR and Camera on iPhone (iPhone의 LiDAR와 Camera를 이용한 실내 공간 안내를 위한 시스템 설계)

  • Junseok Jang;Kwangjae Sung
    • Journal of the Semiconductor & Display Technology
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    • v.23 no.1
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    • pp.71-78
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    • 2024
  • In indoor environments, since global positioning system (GPS) signals can be blocked by obstacles, such as building structure. the performance of GPS-based positioning methods can be degraded because of the loss of GPS signals. To solve this problem, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope, accelerometer, and magnetometer, have been proposed to enhance the positioning accuracy in indoor environments. IMU-based positioning methods can estimate the location of the user by calculating the velocity and heading angle of the user without the help of GPS. However, low-cost MEMS IMUs may lead to drift error and large bias. In addition, positioning errors in IMU-based positioning approaches can be caused by the irrelevant motion of the pedestrian. In this study, we propose an enhanced indoor positioning method that provides more reliable localization results by using the camera, light detection and right (LiDAR), and ARKit framework on the iPhone. Through reliable positioning results and augmented reality (AR) experiences, our indoor positioning system can provide indoor space guidance services.

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Body Temperature Monitoring Using Subcutaneously Implanted Thermo-loggers from Holstein Steers

  • Lee, Y.;Bok, J.D.;Lee, H.J.;Lee, H.G.;Kim, D.;Lee, I.;Kang, S.K.;Choi, Y.J.
    • Asian-Australasian Journal of Animal Sciences
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    • v.29 no.2
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    • pp.299-306
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    • 2016
  • Body temperature (BT) monitoring in cattle could be used to early detect fever from infectious disease or physiological events. Various ways to measure BT have been applied at different locations on cattle including rectum, reticulum, milk, subcutis and ear canal. In other to evaluate the temperature stability and reliability of subcutaneous temperature (ST) in highly fluctuating field conditions for continuous BT monitoring, long term ST profiles were collected and analyzed from cattle in autumn/winter and summer season by surgically implanted thermo-logger devices. Purposes of this study were to assess ST in the field condition as a reference BT and to determine any location effect of implantation on ST profile. In results, ST profile in cattle showed a clear circadian rhythm with daily lowest at 05:00 to 07:00 AM and highest around midnight and rather stable temperature readings (mean${\pm}$standard deviation [SD], $37.1^{\circ}C$ to $37.36^{\circ}C{\pm}0.91^{\circ}C$ to $1.02^{\circ}C$). STs are $1.39^{\circ}C$ to $1.65^{\circ}C$ lower than the rectal temperature and sometimes showed an irregular temperature drop below the normal physiologic one: 19.4% or 36.4% of 54,192 readings were below $36.5^{\circ}C$ or $37^{\circ}C$, respectively. Thus, for BT monitoring purposes in a fever-alarming-system, a correction algorithm is necessary to remove the influences of ambient temperature and animal resting behavior especially in winter time. One way to do this is simply discard outlier readings below $36.5^{\circ}C$ or $37^{\circ}C$ resulting in a much improved mean${\pm}$SD of $37.6^{\circ}C{\pm}0.64^{\circ}C$ or $37.8^{\circ}C{\pm}0.55^{\circ}C$, respectively. For location the upper scapula region seems the most reliable and convenient site for implantation of a thermo-sensor tag in terms of relatively low influence by ambient temperature and easy insertion compared to lower scapula or lateral neck.

Automation of Online to Offline Stores: Extremely Small Depth-Yolov8 and Feature-Based Product Recognition (Online to Offline 상점의 자동화 : 초소형 깊이의 Yolov8과 특징점 기반의 상품 인식)

  • Jongwook Si;Daemin Kim;Sungyoung Kim
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.3
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    • pp.121-129
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    • 2024
  • The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.

Detection of Gaze Direction for the Hearing-impaired in the Intelligent Space (지능형 공간에서 청각장애인의 시선 방향 검출)

  • Oh, Young-Joon;Hong, Kwang-Jin;Kim, Jong-In;Jung, Kee-Chul
    • The KIPS Transactions:PartB
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    • v.18B no.6
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    • pp.333-340
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    • 2011
  • The Human-Computer Interaction(HCI) is a study of the method for interaction between human and computers that merges the ergonomics and the information technology. The intelligent space, which is a part of the HCI, is an important area to provide effective user interface for the disabled, who are alienated from the information-oriented society. In the intelligent space for the disabled, the method supporting information depends on types of disability. In this paper, we only support the hearing-impaired. It is material to the gaze direction detection method because it is very efficient information provide method to present information on gazing direction point, except for the information provide location perception method through directly contact with the hearing-impaired. We proposed the gaze direction detection method must be necessary in order to provide the residence life application to the hearing-impaired like this. The proposed method detects the region of the user from multi-view camera images, generates candidates for directions of gaze for horizontal and vertical from each camera, and calculates the gaze direction of the user through the comparison with the size of each candidate. In experimental results, the proposed method showed high detection rate with gaze direction and foot sensing rate with user's position, and showed the performance possibility of the scenario for the disabled.

Automatic Change Detection Based on Areal Feature Matching in Different Network Data-sets (이종의 도로망 데이터 셋에서 면 객체 매칭 기반 변화탐지)

  • Kim, Jiyoung;Huh, Yong;Yu, Kiyun;Kim, Jung Ok
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.6_1
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    • pp.483-491
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    • 2013
  • By a development of car navigation systems and mobile or positioning technology, it increases interest in location based services, especially pedestrian navigation systems. Updating of digital maps is important because digital maps are mass data and required to short updating cycle. In this paper, we proposed change detection for different network data-sets based on areal feature matching. Prior to change detection, we defined type of updating between different network data-sets. Next, we transformed road lines into areal features(block) that are surrounded by them and calculated a shape similarity between blocks in different data-sets. Blocks that a shape similarity is more than 0.6 are selected candidate block pairs. Secondly, we detected changed-block pairs by bipartite graph clustering or properties of a concave polygon according to types of updating, and calculated Fr$\acute{e}$chet distance between segments within the block or forming it. At this time, road segments of KAIS map that Fr$\acute{e}$chet distance is more than 50 are extracted as updating road features. As a result of accuracy evaluation, a value of detection rate appears high at 0.965. We could thus identify that a proposed method is able to apply to change detection between different network data-sets.