This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.
Journal of the Institute of Convergence Signal Processing
/
v.23
no.3
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pp.166-172
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2022
In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.
Journal of the Institute of Convergence Signal Processing
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v.24
no.2
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pp.119-125
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2023
In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.
Chae-Won Park;Kyung-Mi Kim;Song-Yeon Yoo;Yu-Jin Kim;Kitae Hwang;In-Hwang Jung;Jae-Moon Lee
The Journal of the Institute of Internet, Broadcasting and Communication
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v.24
no.2
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pp.35-40
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2024
In this paper, we validate the practicality of the OnePIC app implemented in the previous study by analyzing the execution and storage performance. The OnePIC app is a camera app that allows you to get a photo with a desired focus after taking photos focused on various places. To evaluate performance, we analyzed distance focus shooting time and object focus shooting time in detail. The performance evaluation was measured on actual smartphone. Distance focus shooting time for 5 photos was around 0.84 seconds, the object detection time was around 0.19 seconds regardless of the number of objects and object focus shooting time for 5 photos was around 4.84 seconds. When we compared the size of a single All-in-JPEG file that stores multi-focus photos to the size of the JPEG files stored individually, there was no significant benefit in storage space because the All-in-JPEG file size was subtly reduced. However, All-in-JPEG has the great advantage of managing multi-focus photos. Finally, we conclude that the OnePIC app is practical in terms of shooting time, photo storage size, and management.
Kim, Keunyong;Kim, Euihyun;Choi, Jun Myoung;Shin, Jisun;Kim, Wonkook;Lee, Kwang-Jae;Son, Young Baek;Ryu, Joo-Hyung
Korean Journal of Remote Sensing
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v.36
no.2_2
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pp.249-261
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2020
Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.
Currently, thanks to the major stride made in developing wired and wireless communication technology, a variety of IT services are available on land. This trend is leading to an increasing demand for IT services to vessels on the water as well. And it is expected that the request for various IT services such as two-way digital data transmission, Web, APP, etc. is on the rise to the extent that they are available on land. However, while a high-speed information communication network is easily accessible on land because it is based upon a fixed infrastructure like an AP and a base station, it is not the case on the water. As a result, a radio communication network-based voice communication service is usually used at sea. To solve this problem, an additional frequency for digital data exchange was allocated, and a ship ad-hoc network (SANET) was proposed that can be utilized by using this frequency. Instead of satellite communication that costs a lot in installation and usage, SANET was developed to provide various IT services to ships based on IP in the sea. Connectivity between land base stations and ships is important in the SANET. To have this connection, a ship must be a member of the network with its IP address assigned. This paper proposes a SANET-CC protocol that allows ships to be assigned their own IP address. SANET-CC propagates several non-overlapping IP addresses through the entire network from land base stations to ships in the form of the tree. Ships allocate their own IP addresses through the exchange of simple requests and response messages with land base stations or M-ships that can allocate IP addresses. Therefore, SANET-CC can eliminate the IP collision prevention (Duplicate Address Detection) process and the process of network separation or integration caused by the movement of the ship. Various simulations were performed to verify the applicability of this protocol to SANET. The outcome of such simulations shows us the following. First, using SANET-CC, about 91% of the ships in the network were able to receive IP addresses under any circumstances. It is 6% higher than the existing studies. And it suggests that if variables are adjusted to each port's environment, it may show further improved results. Second, this work shows us that it takes all vessels an average of 10 seconds to receive IP addresses regardless of conditions. It represents a 50% decrease in time compared to the average of 20 seconds in the previous study. Also Besides, taking it into account that when existing studies were on 50 to 200 vessels, this study on 100 to 400 vessels, the efficiency can be much higher. Third, existing studies have not been able to derive optimal values according to variables. This is because it does not have a consistent pattern depending on the variable. This means that optimal variables values cannot be set for each port under diverse environments. This paper, however, shows us that the result values from the variables exhibit a consistent pattern. This is significant in that it can be applied to each port by adjusting the variable values. It was also confirmed that regardless of the number of ships, the IP allocation ratio was the most efficient at about 96 percent if the waiting time after the IP request was 75ms, and that the tree structure could maintain a stable network configuration when the number of IPs was over 30000. Fourth, this study can be used to design a network for supporting intelligent maritime control systems and services offshore, instead of satellite communication. And if LTE-M is set up, it is possible to use it for various intelligent services.
Journal of the Microelectronics and Packaging Society
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v.24
no.4
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pp.85-90
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2017
The $TiCl_4$ as a blocking material is adsorbed in the mesoporous $TiO_2$ electron transfer layer(ETL) of the Perovskite solar cell to prevent the direct contact between the FTO electrode and the photoactive layer(AL), and facilitate the movement of the electrons between $TiO_2:TiCl_4$ ETL and Perovskite AL to improve the photoelectric conversion efficiency(PCE). The structure of the perovskite solar cell is FTO/$TiO_2:TiCl_4$/Perovskite($CH_3NH_3PbI_3$)/spiro-OMeTAD/Ag. It was investigated that the dipping time of the $TiO_2$ into $TiCl_4$ aqueous solution affects on the photoelectric characteristics of the device. By the dipping for 30 minutes, the PCE of the perovskite solar cell with the $TiO_2:TiCl_4$ ETL was the highest 10.46%, which is 27% higher than the cell with $TiO_2$ ETL. From SEM, EDS, and XRD characterization on the $TiO_2:TiCl_4$ ETL and the perovskite AL, it was measured that the decrease of the porosity of the $TiO_2$ layer, the detection of the Cl component by the $TiCl_4$ adsorption, the cube-type morphology of perovskite AL, and shift of the $PbI_2$ peak of the perovskite AL. From these results, it was confirmed that the $TiO_2:TiCl_4$ ETL and the perovskite AL were formed.
The characteristics of the heavy metal contamination in the soils affected by the tailings of the Palbong mine have been studied. The soils in the studied area consist mostly of loam by the particle size analysis, but a little of it, located near the stream, consist of loamy sand to sandy loam, finally to loam downward. The organic contents of soils are significantly low aoom 2 percent and the pH is in acidic ranging 6.0 $\pm$ 0.1. The samples of the parent rocks, the normal soils, the tailings and the channel deposits from the studied area were chemically analysed. From the result, the heavy metal concenlration of the soils is a little Jow compared with that of the parent rocks, shows the hydrologic process of the surface and the groundwater. The contamination of the tailings from the ore mining are high in lead, copper and arsenic. In the channel deposits the concenlrations of lead and copper are abnormally high but that of arsenic is uniquely low. And most of heavy metal contamination are decreased with the distance from the mine. It is caused by the properties of the surface and the ground water during the process of the heavy metal migration. The correlation-coefficient between sand and silt contents and the concentrations of Cd, Cu and Pb are significant but the amounts of As and Hg are increased with the clay contents. The dispersion of the heavy metals with the distance shows that the concentrations of them in the soils sampled at distance of 100 m to 200 m along the stream started near the Palbong mine are extremely high compared with those from other distances. These discrepancies are significant in Cd, Cu, Pb and Hg, but low in As. All the samples contain below detection limit of Cr+6 In the present stream water the concentrations of the heavy metals are not detected. So, it is interpreted that the concentrations in the soils are caused by the activities of the mining during the operation and have been continued by the dispersion from the tailings since after the closure of the mining, especially by the surface and ground water. The concentrations are diminished with the distance from the mining site, but in the interval of 800-2000 m increases abruptly. In the soil samples counted on the dispersion direction by wind, the lowering of the concentration is relatively uniform with the distance from the mining site. So, the rapid increase of the heavy metal concentrations is presumed to have been caused by the ground-water movement. In the migration of the heavy metals, the groundwater conditions, such as pH, Eh, the contents of colloidal particles, and Mn and Fe oxides are closely involveo. Integrating with these factors, it is interpreted that the groundwater conditions which have caused the heavy metal contamination of the studied area are those that the pH is about 3 in oxidized conditions, the contents of the colloidal particles are low, and Mn and Fe oxides are not involved in the migration of the heavy metals. Meanwhile, the vegetables growing on the soils in the studied area are not affected by the contamination of the heavy metals.
Several research cases using remote sensing methods to analyze changes of storage and dynamics of groundwater aquifer were reviewed in this paper. The status of groundwater storage, in an area with regional scale, could be qualitatively inferred from geological feature, surface water altimetry and topography, distribution of vegetation, and difference between precipitation and evapotranspiration. These qualitative indicators could be measured by geological lineament analysis, airborne magnetic survey, DEM analysis, LAI and NDVI calculation, and surface energy balance modeling. It is certain that GRACE and InSAR have received remarkable attentions as direct utilization from satellite data for quantification of groundwater storage and dynamics. GRACE, composed of twin satellites having acceleration sensors, could detect global or regional microgravity changes and transform them into mass changes of water on surface and inside of the Earth. Numerous studies in terms of groundwater storage using GRACE sensor data were performed with several merits such that (1) there is no requirement of sensor data, (2) auxiliary data for quantification of groundwater can be entirely obtained from another satellite sensors, and (3) algorithms for processing measured data have continuously progressed from designated data management center. The limitations of GRACE for groundwater storage measurement could be defined as follows: (1) In an area with small scale, mass change quantification of groundwater might be inaccurate due to detection limit of the acceleration sensor, and (2) the results would be overestimated in case of combination between sensor and field survey data. InSAR can quantify the dynamic characteristics of aquifer by measuring vertical micro displacement, using linear proportional relation between groundwater head and vertical surface movement. However, InSAR data might now constrain their application to arid or semi-arid area whose land cover appear to be simple, and are hard to apply to the area with the anticipation of loss of coherence with surface. Development of GRACE and InSAR sensor data preprocessing algorithms optimized to topography, geology, and natural conditions of Korea should be prioritized to regionally quantify the mass change and dynamics of the groundwater resources of Korea.
Kim, Tae-Ho;Shin, Hye-Kyeong;Jang, So Yeong;Ryu, Joung-Mi;Kim, Pyeongjoong;Yang, Chan-Su
Korean Journal of Remote Sensing
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v.37
no.6_1
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pp.1773-1784
/
2021
In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.
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