• 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.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.1-6
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• 2022

This paper presents a regionalized time slotted channel hopping (TSCH) slotframe-based aerial data collection using wake-up radio. The proposed scheme aims to minimize the delay and energy consumption when an unmanned aerial vehicle (UAV) collects data from sensor devices in the large-scale service area. To this end, the proposed scheme divides the service area into multiple regions, and determines the TSCH slotframe length for each region according to the number of cells required by sensor devices in each region. Then, it allocates the cells dedicated for data transmission to the TSCH slotframe using the ID of each sensor device. For energy-efficient data collection, the sensor devices use a wake-up radio. Specifically, the sensor devices use a wake-up radio to activate a network interface only in the cells allocated for beacon reception and data transmission. The simulation results showed that the proposed scheme exhibited better performance in terms of delay and energy consumption compared to the existing scheme.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.47-63
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• 2023

Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R² =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.63-80
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• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.520-520
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• 2006

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.322-322
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• 2004

• Journal of Information Technology Services
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• v.15 no.4
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• pp.25-39
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• 2016

The drone is an unmanned aerial vehicle which has no human pilot. Drones can be classified into military drones, commercial drones, and personal drones by usage. Also, drones can be classified from large-sized to nano-sized drone by size and autonomous, remote controlled drone by control type. Especially, military drones can be classified into low-altitude drones, medium-altitude, and high-altitude drones by altitude. Recently, the drone industry is one of the fast growing industries in the world. As drone technologies have become more advanced and cost-effective, Korean government has set its goal to become a top-level country in drone business. However, the government's strict regulation for drone operations is one of the biggest hurdles for the development of the related technologies in Korea and other countries. For example, critical problems for drone delivery can be classified into technical issues and institutional issues. Technical issues include durability, conditional awareness, grasp and release mechanisms, collision avoidance systems, drone operating system. Institutional issues include pilot and operator licensing, privacy rules, noise guidelines, security rules, education for drone police. This study analyzes the trends of the drone industry from the viewpoint of technology and regulation. Also, we define the business areas of drone utilization. Especially, the drone business types or models for public sector are proposed. Drone services or functions promoting public interests need to be aligned with the business reference model of Korean government. To define ten types of drone uses for public sector, we combine the business types of government with the future uses of drones that are proposed by futurists and business analysts. Future uses of drones can be divided into three sectors or services. First, drone services for public or military sectors include early warning systems, emergency services, news reporting, police drones, library drones, healthcare drones, travel drones. Second, drone services for commercial or industrial services include parcel delivery drones, gaming drones, sporting drones, farming and agriculture drones, ranching drones, robotic arm drones. Third, drone services for household sector include smart home drones.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.1
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• pp.118-128
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• 2006

This paper deals with auto-landing guidance system design applicable to Smart UAV(Unmanned Aerial Vehicle). The proposed guidance law generates horizontal position, velocity and altitude commands in the longitudinal channel and heading angle command in the lateral channel to track a predetermined trajectory for automatic landing. The longitudinal guidance commands are derived from an approximated dynamic equations in vertical plane. These longitudinal guidance commands are appropriately distributed to each control input as the flight mode of Smart UAV is changed. The concept of VOR(VHF Omni-directional Range) guidance system is applied to generate the required heading angle commands to eliminate the lateral deviation from the desired trajectory. The performance of the proposed guidance system for Smart UAV is evaluated using the nonlinear simulation. Simulation results show that the proposed guidance system for auto- landing provides good tracking performance along the predetermined landing trajectory.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.1000-1007
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• 2007

In this study, structural vibration analyses of a smart unmanned aerial vehicle (UAV) have been conducted considering dynamic hub-loads of tilt rotor. Practical computational structural dynamics technique based on the finite element method is applied using MSC/NASTRAN. The present UAV(TR-S5-04) finite element model is constructed as a full three-dimensional configuration with different fuel conditions and tilting angles for helicopter, transient and airplane flight modes. In addition, the 3-dimensional supporting equipment structures of electronic devices are considered for vibration analysis. As the results of this study, transient structural displacements and accelerations are presented in detail. Moreover, vibration characteristics of structural parts and installed equipments are investigated for different fuel conditions and tilting angles.