• 제목/요약/키워드: In-Vehicle Network

검색결과 1,406건 처리시간 0.025초

A Low Power Parking Management System for Intelligent Building (인텔리전트 빌딩을 위한 저 전력 주차관리 시스템)

  • Lee, Chang-Ki;Im, Hyung-Kyu
    • The Journal of the Korea institute of electronic communication sciences
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    • 제7권6호
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    • pp.1479-1485
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    • 2012
  • The parking management system can increase driver's convenience with detailed parking information service in the parking lot. At the same time, parking management system consumes non-negligible electrical energy with large amount of sensors, displays and control modules. With the increase in the demand for green and sustainable building design all over the world, it becomes a meaningful issue for parking management system to reduce operating power. This paper presents the preliminary design and estimated results of a parking management system which is optimized to reduce the power consumption mainly on detectors and displays. The system design is based on pre-developed wireless parking detectors, Park Tile and Park Disk. The system has a number of parking space detectors, vehicle count detectors, information displays, guidance terminals and other control units. We have performed system architecture design, communication network design, parking information service scenario planning, battery life regulation and at last operating power estimation. The estimated operating power was 0.93KW per parking-slot, which is 20% of traditional systems. The estimated annual maintenance cost was 18% of traditional systems.

A study on the imputation solution for missing speed data on UTIS by using adaptive k-NN algorithm (적응형 k-NN 기법을 이용한 UTIS 속도정보 결측값 보정처리에 관한 연구)

  • Kim, Eun-Jeong;Bae, Gwang-Soo;Ahn, Gye-Hyeong;Ki, Yong-Kul;Ahn, Yong-Ju
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • 제13권3호
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    • pp.66-77
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    • 2014
  • UTIS(Urban Traffic Information System) directly collects link travel time in urban area by using probe vehicles. Therefore it can estimate more accurate link travel speed compared to other traffic detection systems. However, UTIS includes some missing data caused by the lack of probe vehicles and RSEs on road network, system failures, and other factors. In this study, we suggest a new model, based on k-NN algorithm, for imputing missing data to provide more accurate travel time information. New imputation model is an adaptive k-NN which can flexibly adjust the number of nearest neighbors(NN) depending on the distribution of candidate objects. The evaluation result indicates that the new model successfully imputed missing speed data and significantly reduced the imputation error as compared with other models(ARIMA and etc). We have a plan to use the new imputation model improving traffic information service by applying UTIS Central Traffic Information Center.

Integrating UAV Remote Sensing with GIS for Predicting Rice Grain Protein

  • Sarkar, Tapash Kumar;Ryu, Chan-Seok;Kang, Ye-Seong;Kim, Seong-Heon;Jeon, Sae-Rom;Jang, Si-Hyeong;Park, Jun-Woo;Kim, Suk-Gu;Kim, Hyun-Jin
    • Journal of Biosystems Engineering
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    • 제43권2호
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    • pp.148-159
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    • 2018
  • Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

Development of Deep Learning Based Ensemble Land Cover Segmentation Algorithm Using Drone Aerial Images (드론 항공영상을 이용한 딥러닝 기반 앙상블 토지 피복 분할 알고리즘 개발)

  • Hae-Gwang Park;Seung-Ki Baek;Seung Hyun Jeong
    • Korean Journal of Remote Sensing
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    • 제40권1호
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    • pp.71-80
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    • 2024
  • In this study, a proposed ensemble learning technique aims to enhance the semantic segmentation performance of images captured by Unmanned Aerial Vehicles (UAVs). With the increasing use of UAVs in fields such as urban planning, there has been active development of techniques utilizing deep learning segmentation methods for land cover segmentation. The study suggests a method that utilizes prominent segmentation models, namely U-Net, DeepLabV3, and Fully Convolutional Network (FCN), to improve segmentation prediction performance. The proposed approach integrates training loss, validation accuracy, and class score of the three segmentation models to enhance overall prediction performance. The method was applied and evaluated on a land cover segmentation problem involving seven classes: buildings,roads, parking lots, fields, trees, empty spaces, and areas with unspecified labels, using images captured by UAVs. The performance of the ensemble model was evaluated by mean Intersection over Union (mIoU), and the results of comparing the proposed ensemble model with the three existing segmentation methods showed that mIoU performance was improved. Consequently, the study confirms that the proposed technique can enhance the performance of semantic segmentation models.

Establishing Planning elements of Community Facility considering The Social Weak (사회적 약자를 배려한 공동시설의 계획방향 연구)

  • Jae, Hae-Duek;Lee, Joo-Hyung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • 제16권3호
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    • pp.1753-1763
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    • 2015
  • This study tried to derive the elements of the plan, recognizing the importance of taking into account the social weak when construct community facilities. For these, this study found planning indicator around literature review, then re-established indicators by Focus Group Interview. So it can draw following implication through result of analysis. First, planner considering the social weak should make fair space for harmonious communication between users. physical planning is important, but the building is to be vehicle for the social communication. So it needs to compose program without social elimination. Second, it is important to make participation base for the social weak in community facilities. Finally the reinforce of participation base can be indicator which encourage ownership and locality.

Rapid Management Mechanism Against Harmful Materials of Agri-Food Based on Big Data Analysis (빅 데이터 분석 기반 농 식품 위해인자 신속관리 방법)

  • Park, Hyeon;Kang, Sung-soo;Jeong, Hoon;Kim, Se-Han
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제40권6호
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    • pp.1166-1174
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    • 2015
  • There were the attempts to prevent the spread of harmful materials of the agri-food through the record tracking of the products with the bar code, the partial information tracking of the agri-food storage and the delivery vehicle, or the control of the temperature by intuition. However, there were many problems in the attempts because of the insufficient information, the information distortion and the independent information network of each distribution company. As a result, it is difficult to prevent the spread over the life-cycle of the agri-food using the attempts. To solve the problems, we propose the mechanism mainly to do context awareness, predict, and track the harmful materials of agri-food using big data processing.

An Adaptive Strategy for Providing Dynamic Route Guidance under Non-Recurrent Traffic Congestion (돌발적 교통혼잡발생시 동적경로안내를 위한 적응형 알고리즘개발에 관한 연구)

  • 이상건
    • Proceedings of the KOR-KST Conference
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    • 대한교통학회 1996년도 제30회 학술발표회
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    • pp.81-108
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    • 1996
  • 첨단교통정보시스템(ATIS)의 핵심 요소라 할 수 있는 동적경로안내 시스템(Dynamic Route Guidance System : DRGS)은 운전자가 목적지에 도착하기까지 실시간 교통정보를 토대로 최적경로를 안내해 줌으로써 날로 심화되어 가고 있는 교통혼잡을 최소화할 수 있으리라 기대를 모으고 있다. 특히 교통사고나 긴급도로공사 등으로 인해 발생하는 돌발적 교통혼잡하에서는 DRGS의 역할이 더욱 커질 것으로 예상되고 있다. 본 논문은 돌발적 교통혼잡하에서 보다 효과적인 DRGS의 경로 안내 알고리즘을 개발하는 데 그 목적이 있다. 이를 위해서 우선 하부구조기반(Infrastructure Based) DRGS와 개인차량기반(In-vehicle Based)DRGS의 장단점을 운전자, 교통행정당국, 그리고 교통체계관점에서 비교하였고, 시스템 아키텍쳐와 경로안내 알고리즘간의 상호관계를 규명하였다. 또한 효율적인 경로안내를 위해 사용자 평형(User Equilibrium)경로안내전략과 시스템최적화(System Optimal) 경로안내전략을 이상형 교통망(Idealistic Network)을 통해 비교분석하였다. 여기에는 현재 ITS-America에서 System Architecture 평가를 위해 사용한 INTEGRATION이라는 ITS Simulation Model과 그 통행저항함수를 사용하였다. 이를 토대로 돌발적 교통혼잡상황 아래서 사용자평형 경로안내를 제공할 경우 야기될 수 있는 Braess` Paradox 문제와, 총통행시간을 최소화하기 위한 시스템최적 경로안내를 제공할 경우 일어날 수 있는 사용자 호응도(User Compliance)문제를 동시에 고려한 적응형 동적경로안내 알고리즘을 개발하였다. 여기에는 돌발적 교통혼잡하에서 통행시간을 동적으로 예측하기 위해 이산형 확정적 대기행렬모형(Discrete Deterministic Queueing Model)이 사용되었다. 한편 알고리즘의 효율성을 평가하기 위해 이상형 교통망과, 실제 미국 Virginia 주의 Fairfax County에 소재한 주간 고속도로 66번(I-66)과 인접 교통망의 교통자료를 사용하여 각종 돌발교통 혼잡 상황을 전제로 한 Traffic Simulation과 정보제공시나\리오를 INTEGRATION Model을 이용해 실행하였다. 그 결과 적응형 알고리즘이 개개인의 최단시간 경로를 제공하는 사용자 평형 경로안내전략에 비해 교통혼잡도와 정체시간의 체류정도에 따라 3%에서 10%까지 전체통행시간을 절약할 수 있다는 결론을 얻었다.

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The Study of Implementation of SignBoard Receiving DARC for Vehicle 1. The Implementation of Sign Board Receiving DARC (차량용 FM 부가방송 수신 전광판의 구현에 관한 연구 1. FM 부가방송 수신 전광판의 구현)

  • 최재석;김영길
    • Journal of the Korea Institute of Information and Communication Engineering
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    • 제6권8호
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    • pp.1169-1174
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    • 2002
  • In this paper, we implemented the sign board system that displays user's image, user's sentence, the information from DARC. The existing sign board is displaying only user's image and sentence. Or other existing sign board is displaying the information via CDMA network. However, our system is also able to display the user's message like other system and gain the information more cheap by DARC. This system includes the main processor, the program memory, the external memory, the DARC module and the LED display module. The external memory stores the user's message files and the order file that decides the displaying order of user's file and the DARC information The DARC module extracts the DARC information from FM signal. From the experiment, we could confirm that this system display the DARC information and the user's message by the order file.

Optimal Positioning of Small UAVs for Communication Relay (통신중계를 위한 다수 소형 무인항공기의 최적배치)

  • Jeong, Junho;Kim, Seungkeun;Oh, Hyondong;Suk, Jinyoung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • 제42권6호
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    • pp.461-467
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    • 2014
  • This paper investigates using small UAVs as communications relay nodes for expanding communications links and improving communications quality, primarily for a fleet of ground or navy vessels. An airborne relay in ground/maritime space can effectively connect to units operating over the horizon, beyond normal communication range, or under limited satellite communication environment. Even if the equipment development is mature for communications relay, where to locate UAVs for efficient relay is still a pending question. With this background, this paper will develop high-level deployment algorithms to optimize the location of UAVs for improving the connectivity of a wireless network among a fleet of ground or navy vessels.

Total reference-free displacements for condition assessment of timber railroad bridges using tilt

  • Ozdagli, Ali I.;Gomez, Jose A.;Moreu, Fernando
    • Smart Structures and Systems
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    • 제20권5호
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    • pp.549-562
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    • 2017
  • The US railroad network carries 40% of the nation's total freight. Railroad bridges are the most critical part of the network infrastructure and, therefore, must be properly maintained for the operational safety. Railroad managers inspect bridges by measuring displacements under train crossing events to assess their structural condition and prioritize bridge management and safety decisions accordingly. The displacement of a railroad bridge under train crossings is one parameter of interest to railroad bridge owners, as it quantifies a bridge's ability to perform safely and addresses its serviceability. Railroad bridges with poor track conditions will have amplified displacements under heavy loads due to impacts between the wheels and rail joints. Under these circumstances, vehicle-track-bridge interactions could cause excessive bridge displacements, and hence, unsafe train crossings. If displacements during train crossings could be measured objectively, owners could repair or replace less safe bridges first. However, data on bridge displacements is difficult to collect in the field as a fixed point of reference is required for measurement. Accelerations can be used to estimate dynamic displacements, but to date, the pseudo-static displacements cannot be measured using reference-free sensors. This study proposes a method to estimate total transverse displacements of a railroad bridge under live train loads using acceleration and tilt data at the top of the exterior pile bent of a standard timber trestle, where train derailment due to excessive lateral movement is the main concern. Researchers used real bridge transverse displacement data under train traffic from varying bridge serviceability levels. This study explores the design of a new bridge deck-pier experimental model that simulates the vibrations of railroad bridges under traffic using a shake table for the input of train crossing data collected from the field into a laboratory model of a standard timber railroad pile bent. Reference-free sensors measured both the inclination angle and accelerations of the pile cap. Various readings are used to estimate the total displacements of the bridge using data filtering. The estimated displacements are then compared to the true responses of the model measured with displacement sensors. An average peak error of 10% and a root mean square error average of 5% resulted, concluding that this method can cost-effectively measure the total displacement of railroad bridges without a fixed reference.