• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.6
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• pp.573-581
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• 2018

The purpose of this study is to evaluate the fixed wing type domestic UAV for monitoring of algae bloom in aquatic environment. The UAV used in this study is operated automatically in-flight using an automatic navigation device, and flies along a path targeting preconfigured GPS coordinates of desired measurement sites input by a flight path controller. The sensors used in this study were Sequoia multi-spectral cameras. The photographed images were processed using orthomosaics, georeferenced digital surface models, and 3D mapping software such as Pix4D. In this study, NDVI(Normalized distribution vegetation index) was used for estimating the concentration of chlorophyll-a in river. Based on the NDVI analysis, the distribution areas of chlorophyll-a could be analyzed. The UAV image was compared with a airborne image at a similar time and place. UAV images were found to be effective for monitoring of chlorophyll-a in river.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.16-22
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• 2011

This paper presents the potential of in-vehicle data recorder system for monitoring aggressive driving patterns and providing feedback to drivers on their on road behaviour. This system can detect 10 risky types of drivers' driving patterns such as aggressive lane change, sudden brakes and turns with acceleration etc. Vehicle dynamics simulation and vehicle road test have been performed in order to develop driving pattern recognition algorithms. Recorder systems are installed to 50 buses in a single company. Drivers' driving behaviour are monitored for 1 month. The drivers' risky driving data collected by the system are analyzed. Aggressive lane change in 50km/h below is a cause in overwhelming majority of risky driving pattern.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.96.2-96.2
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• 2010

EV(Electric Vehicle) 차량에서 BMS(Battery Management System) 은 모터에 공급되는 고전압 배터리의 충전상태를 감지하여 VCU(Vehicle Control Unit)에 전송하게 된다. VCU에서는 배터리의 충전상태를 확인하여 모터 구동 전략을 수립하여 각 제어기에 전송하게 된다. 위와 같이 EV에서 배터리 충전상태를 정확하게 감지하지 못한다면, 모터 구동을 위한 전략 수립에 많은 제약이 따르게 된다. 정확한 배터리 충전 상태를 감지하기 위해서는 배터리 각 셀의 전압/전류/온도 등을 측정하여 연산에 의해 결정된다. 그 중 셀 전압 측정 방식은 Photomos relay를 이용한 방식으로 하드웨어적인 오차에 ${\pm}$수십mV보다 더둑 더 정밀하게 측정할 수 있는 방법이 없었다. 하지만, 셀 전압 측정 정밀도를 향상시키기 위해 신규로 개발된 battery monitoring IC를 이용한 BMS의 H/W 개발에 대해 설명할 것이다. 또한, Monitoring IC를 이용한 BMS의 셀 전압 측정 정밀도를 얼마나 개선시킬 수 있는지에 대해 연구하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.1
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• pp.67-74
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• 2009

In this paper, we constructed Embedded web-server to be monitored and controlled for intelligent vehicle on the base of embedded system and Zigbee wireless communication. By interfacing main controller and embedded system with ECU including every information of vehicle, it is possible to monitor the cruising information of vehicle, and sensor signal added to inside and outside of vehicle is transferred to embedded system through Zigbee communication. Web-server is constructed using embedded system, that's why the access to vehicle is possible using PC or mobile instrument, and the real-time check and control of vehicle is possible as well.

• Steel and Composite Structures
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• v.46 no.6
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• pp.731-744
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• 2023

Vehicle load information is an important role in operating and ensuring the structural health of cable-stayed bridges. In this regard, an efficient and economic method is proposed for vehicle load detection based on the observed cable tension and vehicle position using a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), a robust program for modeling and considering both geometric and material nonlinearities of bridge structures subjected to vehicle load with low computational costs. With the superiority of GNN, the proposed model is demonstrated to precisely capture complex nonlinear correlations between the input features and vehicle load in the output. Four popular machine learning methods including artificial neural network (ANN), decision tree (DT), random forest (RF), and support vector machines (SVM) are refereed in a comparison. A case study of a cable-stayed bridge with the typical truck is considered to evaluate the model's performance. The results demonstrate that the GNN-based model provides high accuracy and efficiency in prediction with satisfactory correlation coefficients, efficient determination values, and very small errors; and is a novel approach for vehicle load detection with the input data of the existing monitoring system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.133-140
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• 2017

In this paper, we has proposed an automatic vehicle monitoring system based on computer vision technology. The real-time display system has displayed a system that can be performed in automatic monitoring and control while meeting the essential requirements of ITS. Another advantage has that for a powerful vehicle tracking, the main obstacle handing system, which has the shadow tracking of moving objects. In order to obtain all kinds of information from the tracked vehicle image, the vehicle must be clearly displayed on the surveillance screen. Over time, it's necessary to precisely control the vehicle, and a three-dimensional model-based approach has been also necessary. In general, each type of vehicle has represented by the skeleton of the object or wire frame model, and the trajectory of the vehicle can be measured with high precision in a 3D-based manner even if the system has not running in real time. In this paper, we has applied on segmentation method to vehicle, background, and shadow. The validity of the low level vehicle control tracker was also detected through speed tracking of the speeding car. In conclusion, we intended to improve the improved tracking method in the tracking control system and to develop the highway monitoring and control system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.31-37
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• 2012

In this paper, we present a smart grid monitoring system connected with electric vehicle charging system using anti-islanding method. Electric vehicles can be charged through remote control of smart grid monitoring system and the charging process may be more stable and more efficient by wireless communication between the Local Area Module and End Modules. It is illustrated by some experiments that electric vehicle charging process may not be interrupted without any serious fault even though the islanding phenomena occurred in the grid if the presented monitoring system was applied to the smart grid system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.3
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• pp.285-290
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• 2006

In a Vehicle, Safety is the most important factor for drivers. It is well known that tire pressure lower than normal reduces the safety of the vehicle. In a consideration of active safety, tire pressure monitoring system is absolutely required. Tire pressure monitoring using in-tire pressure sensors with an RE data link have proven to be best approach to measuring tire pressure over the widest range of operating conditions. In this paper, we describe the parameters of TPMS, the characteristic of tire pressure and temperature compensation. These are the main factors to design the decision logic. We will show the guidelines for TPMS logic development considering environment variables and vehicle conditions.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.42-47
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• 2008

It is important for national safety that tank lorry or bulk lorry which is carrying toxic gas or explosive materials should be monitored during the maneuvering from starting point to destination as well as vehicle or tank status. Therefore, we propose a safety monitoring system for tank lorry to check driving condition and the vehicle status. We studied the integration of central control system with in-vehicle computer system connected with various sensors for monitoring through a communication network.