• 전자통신동향분석
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• 제38권6호
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• pp.31-40
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• 2023

Given recent accidents involving autonomous vehicles, driver monitoring technology related to the transition of control in autonomous vehicles is gaining prominence. Driver status monitoring systems recognize the driver's level of alertness and identify possible impairments in the driving ability owing to conditions including drowsiness and distraction. In autonomous vehicles, predictive factors for the transition to manual driving should also be included. During traditional human driving, monitoring the driver's status is relatively straightforward owing to the consistency of crucial cues, such as the driver's location, head orientation, gaze direction, and hand placement. However, monitoring becomes more challenging during autonomous driving because of the absence of direct manual control and the driver's engagement in other activities, which may obscure the accurate assessment of the driver's readiness to intervene. Hence, safety-ensuring technology must be balanced with user experience in autonomous driving. We explore relevant global and domestic regulations, the new car assessment program, and related standards to extract requirements for driver status monitoring. This kind of monitoring can both enhance the autonomous driving performance and contribute to the overall safety of autonomous vehicles on the road.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.489-492
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• 2016

Transportation in the logistics, many business organizations are engaged in monitoring and tracking the vehicles in order to improve logistics services, reduce expenses and secure security in cargo transportation. It is saving time and money by tracking and monitoring vehicles which transport cargo in supply chain of logistics. Therefore the main issue of delivery flow is to improve services, and ensure the safety in transportation system. This article suggests the tracking and monitoring model to keep safety transports on ICT network. It focuses on precise delivery control by monitoring and tracking vehicles to save time and costs. The status of product movement is analyzed for proper decision making. The vehicle embedded with RFID is automatically tracked in the movement process by tracking and monitoring model. The main role keeps safety tracking to reduce costs and to deliver products at proper time and location.

• Structural Monitoring and Maintenance
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• 제11권2호
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• pp.149-171
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• 2024

Drive-by monitoring (also known as indirect monitoring or mobile sensing) of bridges has obvious advantages when compared to other approaches of Structural Health Monitoring. The underlying concept involves leveraging the coupling between the vertical vibrations of the bridge and those generated in the passing vehicle. In this scenario, the vehicle serves as both the initiator and recipient of the vibrations, which can provide information on the structural condition of the bridge. In the literature, a wide range of methods has been proposed, primarily focused on highway bridges. However, limited research has been published to assess the suitability of indirect methods for monitoring railway bridges, bounded to numerical studies based on theoretical simulations and, rarely, on experimental investigations. The aim of this work is to contribute to filling this gap and explore the feasibility of implementing drive-by monitoring for railway bridges using in-service vehicles and discuss its potential applicability, from theoretical and practical point of view, with illustration through real case studies from the Moroccan railway network.

• 한국정보통신학회논문지
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• 제18권3호
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• pp.713-718
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• 2014

본 논문에서는 국내 겨울철 폭설과 같은 재난 발생시 각 지자체 별로 확보되어 있는 제설차량을 효과적으로 운영하고 제설현장 정보 및 차량의 이동성을 실시간으로 모니터링하여 폭설 재난현장에 대해 신속히 대처할 수 있는 실시간 모니터링 시스템을 제안하였다. 또한, 제안 시스템에서 중계단말의 효과적인 진단 및 각종 제어정보를 분석할 수 있는 중계단말 분석 도구를 설계하였다. 제안한 시스템은 폭설시 제설차량의 위치정보와 제설작업을 위한 차량제어정보 및 제설작업 상태정보를 실시간으로 모니터링 함으로써 짧은 시간에 효과적인 작업진행과 실시간 이동경로추적을 통하여 폭설 재난상황에 대한 효과적인 응급대처가 가능한 시스템이다.

• Advances in Computational Design
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• 제5권1호
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• pp.91-109
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• 2020

Over the past few decades, the impact of natural, manmade and natech (natural hazard triggering technological disasters) disasters has been devastating, affecting over 4.4 billion people. In spite of recent technological advances, the increasing frequency and intensity of natural disasters and the escalation of manmade threats is presenting a number of challenges that warrant immediate attention. This paper explores the integration of drones or Unmanned Aerial Vehicles (UAV's) into infrastructure monitoring and post-disaster assessment. Through reviewing some of the recent disasters, effectiveness of utilizing UAV's in different stages of disaster life cycle is demonstrated and needed steps for successful integration of UAV's in infrastructure monitoring, hazard mitigation and post-incident assessment applications are discussed. In addition, some of the challenges associated with implementing UAV's in disaster monitoring, together with research needs to overcome associated knowledge gaps, is presented.

• 경영과학
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• 제21권3호
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• pp.115-127
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• 2004

In this paper, we describe an intelligent monitoring and control system for pick-up/delivery service. This system applies geographical information system(GIS), global positioning system(GPS) and wireless communication technologies for managing pick-up/delivery operations more effectively. It consists of three subsystems, pick-up/delivery sequence planning system, pick-up/delivery monitoring system, and PDA execution system. Pick-up/delivery sequence planning system generates routes and schedules for pick-up/delivery using GIS and optimization techniques. Pick-up/delivery monitoring system monitors current positions of vehicles and actual pick-up/delivery results as compared with planned routes and visit times, while PDA execution system transmits information for vehicles positions and actual pick-up/delivery results using GPS and wireless communication technologies. The intelligent monitoring and control system is currently being used for the pick-up parcel service in a local post office of Korea Post.

• Journal of Power Electronics
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• 제11권4호
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• pp.424-429
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• 2011

In this paper, the simulator of an on-line monitoring system for the range extender electric vehicle has been developed. The messages from the four control modules, the air pressure and fuel level sensors data, and the on/off switching states of 31 indicator lamps can be received through the control area network (CAN), and displayed on the graphic panel. The simulator was designed using the four DSP boards, variable resistors, and toggle switches instead of the four control modules, sensors, and switching state of indicator lamps on an actual series hybrid electric vehicle (SHEV) bus, respectively. The performance of the monitoring technologies was verified with the simulator at the laboratory, and then it was tested on an actual SHEV bus. The simulator is very useful at the initial development of the monitoring system at the hybrid-type or electrical vehicles.

• Smart Structures and Systems
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• 제28권6호
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• pp.799-810
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• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1505-1515
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• 2016

The age of autonomous vehicles has come according to development of high performance sensing and artificial intelligence technologies. And importance of the vehicle's surrounding environment sensing and observation is increasing accordingly because of its stability and control efficiency. In this paper we propose an integrated platform for efficient networking, analysis and monitoring of multiple sensing data on the vehicle that are equiped with various automotive sensors such as GPS, weather radar, automotive radar, temperature and humidity sensors. From simulation results, we could see that the proposed platform could perform realtime analysis and monitoring of various sensing data that were observed from the vehicle sensors. And we expect that our system can support drivers or autonomous vehicles to recognize optimally various sudden or danger driving environments on the road.

• Smart Structures and Systems
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• 제9권3호
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• pp.287-301
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• 2012

It is well known that overloaded vehicles may cause severe damages to bridges, and how to estimate and evaluate the status of the overloaded vehicles passing through bridges become a challenging problem. Therefore, based on the monitored strain data from a structural health monitoring system (SHM) installed on a bridge, a method is recommended to identify and analyze the probability of overloaded vehicles. Overloaded vehicle loads can cause abnormity in the monitored strains, though the abnormal strains may be small in a concrete continuous rigid frame bridge. Firstly, the abnormal strains are identified from the abundant strains in time sequence by taking the advantage of wavelet transform in abnormal signal identification; secondly, the abnormal strains induced by heavy vehicles are picked up by the comparison between the identified abnormal strains and the strain threshold gotten by finite element analysis of the normal heavy vehicle; finally, according to the determined abnormal strains induced by overloaded vehicles, the statistics of the overloaded vehicles passing through the bridge are summarized and the whole probability of the overloaded vehicles is analyzed. The research shows the feasibility of using the monitored strains from a long-term SHM to identify the information of overloaded vehicles passing through a bridge, which can help the traffic department to master the heavy truck information and do the damage analysis of bridges further.