• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7C
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• pp.544-553
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• 2012

A vehicle localization technology is an essential component to support many smart-vehicle applications, e.g. collision warning, adaptive cruise control, and so on. In this paper, we present a new vehicle localization algorithm based on the fusion of the sensing estimates from the local sensors and the GPS estimates from the inter-vehicle communications. The proposed algorithm consists of the greedy location data mapping algorithm and the position refinement algorithm. The former maps a sensing estimate with a GPS estimate based on the distance between themselves, and then the latter refines the GPS estimate of the subject vehicle based on the law of large numbers. From the numerical results, we demonstrate that the accuracy of the proposed algorithm outperforms that of the existing GPS estimates by at least 30 % in the longitudinal direction and by at least 60% in the lateral direction.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.1 no.1
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• pp.31-40
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• 2020

The rapid development of technologies in unmanned aerial vehicles (UAVs) has led to their use in various areas. UAVs are mainly used for commercial purposes, but their utilization is increasingly important in other areas because their operation cost is less than satellites and aerial imaging. The utilization of UAVs in the environment/ecology area is relatively new. Therefore, identifying the trends of UAV-related spatial information is significant in basic research for UAV utilization. This study quantitatively identified domestic and international research trends related to UAV utilization and analyzed research areas. An attempt was also made to identify upcoming UAV-related topics in the environment/ecology research field using text mining to analyze the bibliographic information of global research literature. Domestic UAV-related studies were classified into seven clusters where basic research on "UAV technology/industry trends" was abundant, and studies on data collection and analysis through UAV remote sensing technology have increased since 2015. Eight clusters were identified for international studies where the most active research area international was "remote sensing technology/data analysis". In addition, Canopy, Classification, Forest, Leaf Area Index, Normalized Difference Vegetation Index, Temperature, Tree, and Atmosphere appeared as the main keywords related to environment and ecology. The appearance frequencies and association strengths were high because the advancement in UAV optical sensor technology and the rapid development of image processing technology enabled the acquisition of data that could not be obtained from existing spatial information. They are recognized as future research topics as related domestic studies have begun corresponding to international research.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.21-28
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• 2017

The main goal of this paper is to assess application of UAV (Unmanned Aerial Vehicle) remote sensing and GIS based images in detection and measuring of rice field drought area in South Korea. Drought is recurring feature of the climatic events, which often hit South Korea, bringing significant water shortages, local economic losses and adverse social consequences. This paper describes the assesment of the near-realtime drought damage monitoring and reporting system for the agricultural drought region. The system is being developed using drought-related vegetation characteristics, which are derived from UAV remote sensing data. The study area is $3.07km^2$ of Wonbuk-myeon, Taean-gun, Chungnam in South Korea. UAV images were acquired three times from July 4 to October 29, 2015. Three images of the same test site have been analysed by object-based image classification technique. Drought damaged paddy rices reached $754,362m^2$, which is 47.1 %. The NongHyeop Agricultural Damage Insurance accepted agricultural land of 4.6 % ($34,932m^2$). For paddy rices by UAV investigation, the drought monitoring and crop productivity was effective in improving drought assessment method.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.101-116
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• 1995

The fact that the demands on traffic data collection are imposed by economic and safety considerations raisese the question of the potential for complementing existing traffic data collection programs with satellite data. Evaluating and monitoring traffic characteristics is becoming increasingly important as worsening congestion, declining economic situations, and increasing environmental sensitivies are forcing the government and municipalities to make better use of existing roadway capacities. The present system of using automatic counters at selected points on highways works well from a temporal point of view (i.e., during a specific period of time at one location). However, the present system does not cover the spatial aspects of the entire road system (i.e., for every location during specific periods of time); the counters are employed only at points and only on selected highways. This lack of spatial coverage is due, in part, to the cost of the automatic counters systems (fixed procurement and maintenance costs) and of the personal required to deploy them. The current procedure is believed to work fairly well in the aggregate mode, at the macro level. However, at micro level, the numbers are more suspect. In addition, the statistics only work when assuming a certain homogenity among characteristics of highways in the same class, an assumption that is impossible to test whn little or no data is gathered on many of the highways for a given class. In this paper, a remote sensing system as complement of the existing system is considered and implemented. Since satellite imagery with high resolution is not available, digitized panchromatic imagery acquired from an aircraft platform is utilized for initial test of the feasibility and performance capability of remote sensing data. Different levels of imagery resolutions are evaluated in an attempt to determine what vehicle types could be classified and counted against a background of pavement types, which might be expected in panchromatic satellite imagery. The results of a systematic study with three different levels of resolutions (1m, 2m and 4m) show that the panchromat ic reflectances of vehicles and pavements would be distributed so similarly that it would be difficult to classify systematically and analytically remotely sensing vehicles on pavement within panchromatic range. Anaysis of the aerial photographs show that the shadows of the vehicles could be a cue for vehicle detection.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.6
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• pp.91-97
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• 2015

The Unmanned Aerial Vehicles (UAVs) have several advantages over conventional RS techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude i.e. 80~400 m, they can obtain good quality images even in cloudy weather. Therefore, they are ideal for acquiring spatial data in cases of small agricultural field with mixed crop, abundant in South Korea. This paper discuss the use of low cost UAV based remote sensing for classifying crops. The study area, Gochang is produced by several crops such as red pepper, radish, Chinese cabbage, rubus coreanus, welsh onion, bean in South Korea. This study acquired images using fixed wing UAV on September 23, 2014. An object-based technique is used for classification of crops. The results showed that scale 250, shape 0.1, color 0.9, compactness 0.5 and smoothness 0.5 were the optimum parameter values in image segmentation. As a result, the kappa coefficient was 0.82 and the overall accuracy of classification was 85.0 %. The result of the present study validate our attempts for crop classification using high resolution UAV image as well as established the possibility of using such remote sensing techniques widely to resolve the difficulty of remote sensing data acquisition in agricultural sector.

• Smart Structures and Systems
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• v.31 no.3
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• pp.301-309
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• 2023

Tilt is a key indicator of structural safety. Real-time monitoring of tilt responses helps to evaluate structural condition, enable cost-effective maintenance, and enhance lifetime resilience. This paper presents a prototype wireless sensing system for structural tilt measurement. Long range (LoRa) technology is adopted by the sensing system to offer long-range wireless communication with low power consumption. The sensor integrates a gyroscope and an accelerometer as the sensing module. Although tilt can be estimated from the gyroscope or the accelerometer measurements, these estimates suffer from either drift issue or high noise. To address this challenging issue and obtain more reliable tilt results, two sensor fusion algorithms, the complementary filter and the Kalman filter, are investigated to fully exploit the advantages of both gyroscope and accelerometer measurements. Numerical simulation is carried out to validate and compare the sensor fusion algorithms. Laboratory experiment is conducted on a simply supported beam under moving vehicle load to further investigate the performance of the proposed wireless tilt sensing system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.107-117
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• 2020

With the recent development of autonomous vehicles, various sensors installed in vehicles have become common, and big data generated from those sensors is increasingly being used in the transportation field. In this study, we proposed a grid index method to efficiently process real-time vehicle sensing big data and public data such as road weather. The applicability and effect of the proposed grid space division method and grid ID generation method were analyzed. We created virtual data based on DTG data and mapped to the road link based on coordinates. As a result of analyzing the data processing speed in grid index method, the data processing performance improved by more than 2,400 times compared to the existing link unit processing method. In addition, in order to analyze the efficiency of the proposed technology, the virtually generated data was mapped and visualized.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.81-87
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• 2023

SAE J2601 and SAE J2799, the communication protocols between a hydrogen refueling station and a fuel cell electric vehicle, only cover hydrogen charging. In this paper, we measure the hydrogen detection, current, and voltage of a fuel cell electric vehicle and transmit the sensor data to the hydrogen refueling station by changing the WiFi protocol. A small-scale laboratory model was built using Raspberry Pi for sensing, controlling, and transmitting sensor data of a fuel cell electric vehicle. The sensor data was stored in the database of the hydrogen refueling station, and a dashboard was configured using Grafana to analyze the stored data. When hydrogen is detected, the dispenser valve of the hydrogen refueling station is locked. Then, we measured the average transmission delay according to the WiFi protocol. The results showed that IEEE 802.11a is the most suitable WiFi protocol for transmitting sensor data between the hydrogen refueling station and the fuel cell electric vehicle.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.597-598
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• 2018

Recently, the future traffic system is mainly aiming traffic safety by collecting, managing and providing traffic information using traffic system. But In this paper, we propose traffic safety using traffic safety mark which is currently utilized transportation infrastructure. The vehicle receives the sensed data with the traffic safety sign as a host, and carries out communication between the vehicles or the infrastructure. By using the information of sensing data, various information can be obtained. In addition to the construction section, traffic accidents can also be utilized. Therefore, this paper is designed to simplify the frame of sensing data and contribute to traffic safety through continuous research.