• Korean Journal of Remote Sensing
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• v.30 no.3
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• pp.351-366
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• 2014

The aim of this study was to develop software for beach litter detection that includes a Graphical User Interface (GUI) and uses images taken by a micro-unmanned aerial vehicle. Videos were taken over Doomo pebble beach, Sogye pebble beach, and Heungnam sand beach on the northeast coast of Geojedo (Geoje Island), Korea. Still images of actual beach litter were obtained from the videos. The image processing involved preprocessing, morphological image processing, and image recognition. Comparison with still images showing beach litter demonstrated that the software could generally detect litter larger than 50 cm in size such as Styrofoam buoys and circular fish traps (excluding small pixel-size ropes). Combining the proposed method with the conventional surveying approach is expected to enhance the accuracy of beach litter detection. The new technique will also aid in predicting the amount of beach litter generated along coastlines, which is currently difficult to monitor.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.24-34
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• 2011

An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for human. UA V s are currently employed in many military missions such as reconnaissance, surveillance, enemy radar jamming, decoying, suppression of enemy air defense (SEAD), fixed and moving target attack, and air-to-air combat. UAVs also are employed in a number of civilian applications such as monitoring ozone depletion, inclement weather, traffic congestion, and taking images of dangerous territory. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$-PGA (A-star with Post Smoothing-Parallel Genetic Algorithm) for an UAV's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and TSP (Traveling Salesman Problem). A path planning algorithm for UAV is applied by transforming MRPP into SPP (Shortest Path Problem).

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.181-186
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• 2016

Recently, the surveillance system research has focused because Unmanned Aerial Vehicle(UAV) has the ability to monitor wide area. When the wide area are monitored, controlling UAVs repeatedly by pilots invokes the cost problem to operate UAVs. If monitoring path can be defined in advance, the cost problem can be solved by controlling UAVs autonomously based on the monitoring path. The traditional approach generates multiple motor primitives based on flied GPS locations. However, the monitoring points by UAVs are not considered by the generated motor primitives, the surveillance by UAVs is not performed properly. This paper proposes a motor primitive structure for surveillance UAVs to be flied autonomously. Motor primitives are generated automatically by setting surveillance points to denote surveillance targets accurately.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.87-96
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• 2016

Red tide, causes aquaculture industry the damages in Korea every summer, was usually detected by using satellite, aquaculture information was difficult to detect by using satellite. Therefore, we suggests the method for detecting the red tide using the coastal observation and the product from the unmanned aerial Vehicle. As a result, we obtained the high resolution unmanned aerial Vehicle images, detected the red tide by using the unsupervised classification from the true color images and the simple algorithm from the RGB color images. Compared the previous color images, unmanned aerial Vehicle images were clearly classified the ocean color, we were able to identify the red tide distribution in sea surface. These methods were determined to accurately monitor the red tide distribution on the aquaculture fields in the coastal waters where is established the aquaculture.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.495-502
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• 2016

Italian Ryegrass (IRG), which is known as high yielding and the highest quality winter annual forage crop, is grown in mid-south area in Korea. The objective of this study was to evaluate the use of unmanned aerial vehicle (UAV) for the monitoring IRG growth. Unmanned aerial vehicle imagery obtained from middle March to late May in Nonsan, Chungcheongnam-do. Unmanned aerial vehicle imagery corrected geometrically and atmospherically to calculate normalized difference vegetation index (NDVI). We analyzed the relationships between $NDVI_{UAV}$ of IRG and biophysical measurements such as plant height, fresh weight, and dry weight over an entire IRG growth period. The similar trend between $NDVI_{UAV}$ and growth parameters was shown. Correlation analysis between $NDVI_{UAV}$ and IRG growth parameters revealed that $NDVI_{UAV}$ was highly correlated with fresh weight (r=0.988), plant height (r=0.925), and dry weight (r=0.853). According to the relationship among growth parameters and $NDVI_{UAV}$, the temporal variation of $NDVI_{UAV}$ was significant to interpret IRG growth. Four different regression models, such as (1) Linear regression function, (2) Linear regression through the origin, (3) Power function, and (4) Logistic function were developed to evaluate the relationship between temporal $NDVI_{UAV}$ and measured IRG growth parameters. The power function provided higher accurate results to predict growth parameters than linear or logistic functions using coefficient of determination. The spatial distribution map of IRG growth was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when $NDVI_{UAV}$ was applied to power function. From these results, $NDVI_{UAV}$ can be used as a new tool for monitoring IRG growth.

• Journal of Advanced Navigation Technology
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• v.8 no.2
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• pp.105-111
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• 2004

This paper describes the design of navigation system for an unmanned target drone which is operated by Korean army as for anti-air gun shooting training. Current target drone is operated by pilot control of on-board servo motor via remote control system. Automatic flight control system for the target drone greatly reduces work load of ground pilot and can increase application area of the drone. Most UAVs being operated nowdays use high-priced sensors as AHRS and IMU to measure the attitude, but those are costly. This paper introduces the development of low-cost automatic flight control system with low-cost sensors. The integrated automatic flight control system has been developed by integrating combining power module, switching module, monitoring module and RC receiver as an one module. The performance of navigation for low cost unmanned aerial vehicle, unmanned target drone as our test bed in this paper is verified by both Hardware in the loop simulation(HILS) to test performance of GPS as GPS output frequency high and results of flight test.

• Journal of the Geological Society of Korea
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• v.54 no.5
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• pp.501-511
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• 2018

Geoparks are worth preserving in an environmentally and heritage. Monitoring and public attention are essential for the conservation and protection of geoparks. The use of Unmanned Aerial Vehicles and the Structure from Motion algorithm enables effective monitoring of geoparks that are difficult to manage due to their wide range of manpower, and various spatial data derived from SfM can be utilized to improve awareness of geoparks that have been lacking. In order to prove this, firstly, we created the 3D spatial data by using the UAV and the SfM algorithm, which is one of the National geoparks of the Hantan-Imjin River area. Using this 3D data for Virtual Reality and 3D printing. After that, we verified the possibility of promoting the geopark through a simple online survey. Finally, we propose a method to utilize all the generated data from each step to promote and research for geoparks.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.11-19
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• 2012

Due to existing infrastructure to collect traffic information was constructed to expressway and national highway, we cannot precisely know traffic situation for their surrounding area. Therefore, it is difficult to provide reliable traffic information to users using navigation and smartphone. In this research, we collected aerial images by using unmanned airship capable of wide-area monitoring and proposed a method extracting vehicle speed from the collected data. And, we performed experiments to verify the accuracy of extracted vehicle speed. Our method proposed in this research can be used to extract a new approach of traffic information according to increased demand of traffic monitoring. We expect that our method will become a new research trend in traffic information application.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.457-464
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• 2017

The large breeding of algae in rivers has caused the algal bloom and has becoming a serious national problem for the safety of water sources. Therefore, in order to supply stable water resources through securing clean water, it is necessary to develop technology for prevention of water pollution caused by algal bloom. The purpose of this study is to improve the water quality management ability of river by applying the algal bloom detection technique using UAV. Unmanned aerial images were acquired for the Dodong in the middle region of the Nakdong River where algal bloom are frequent. In addition, the phytoplankton concentration was acquired through the sampling of algal bloom and the examination of water quality. Correlation between phytoplankton concentrations and the results of applying the algal bloom index to the Unmanned aerial images showed a strong positive correlation. The remote sensing method suggested in this study is expected to improve the initial response capability of river water pollution.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.77-84
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• 2022

In this paper, we propose a system for monitoring air pollutants such as fine dust using an unmanned aerial vehicle capable of autonomous navigation. The existing air quality management system used a method of collecting information through a fixed sensor box or through a measurement sensor of a drone using a control device. This has disadvantages in that additional procedures for data collection and transmission must be performed in a limited space and for monitoring. In this paper, to overcome this problem, a GPS module for location information and a PMS7003 module for fine dust measurement are embedded in an unmanned aerial vehicle capable of autonomous navigation through flight information designation, and the collected information is stored in the SD module, and after the flight is completed, press the transmit button. It configures a system of one-stop structure that is stored in a remote database through a smartphone app connected via Bluetooth. In addition, an HTML5-based web monitoring page for real-time monitoring is configured and provided to interested users. The results of this study can be utilized in an environmental monitoring system through an unmanned aerial vehicle, and in the future, various pollutants measuring sensors such as sulfur dioxide and carbon dioxide will be added to develop it into a total environmental control system.