• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.2
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• pp.73-79
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• 2021

Recently there are growing interests on the energy conservation and emission reduction. In the fields of architecture and civil engineering, the energy monitoring of structures is required to response the energy issues. In perspective of thermal monitoring, thermal images gains popularity for their rich visual information. With the rapid development of the drone platform, aerial thermal images acquired using drone can be used to monitor not only a part of structure, but wider coverage. In addition, the stereo photogrammetric process is expected to generate 3D point cloud with thermal information. However thermal images show very poor in resolution with narrow field of view that limit the use of drone-based thermal photogrammety. In the study, we aimed to generate 3D thermal point cloud using visible and thermal images. The visible images show high spatial resolution being able to generate precise and dense point clouds. Then we extract thermal information from thermal images to assign them onto the point clouds by precisely establishing photogrammetric collinearity between the point clouds and thermal images. From the experiment, we successfully generate dense 3D thermal point cloud showing 3D thermal distribution over the building structure.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.141-150
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• 2023

Currently, various companies are actively participating in research and development of drone delivery services. Existing studies do not comprehensively provide integrated functions for future drone delivery services such as mission automation, customer verification, and overcoming performance limitations, which can lead to high manpower demand, reduced user service trust, and potentially overloading low-end devices. Therefore, this study proposes a drone mission automation system (DMAS) using EdgeCPS technology to provide the three aforementioned functions in an integrated manner. Real-world experiments were conducted to evaluate the proposed system, demonstrating that the DMAS components operate according to the specified roles in the delivery scenario. In addition, the system achieved user verification with a similarity of more than 90% in the process of receiving the product, and verified a faster inference speed and a lower resource share than the existing method.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.740-745
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• 2023

This study proposes the development of an antenna tracker system using a satellite system to stabilize the communication status of drones and extend the communication distance. The location information of the drone and the ground station was used to maximize communication gain in the general fixed antenna method between the ground station and the drone. We developed a tracker system that can automatically and continuously aim the ground station's antenna at the drone. It is expected that the use of antenna trackers will improve the stabilization of communication conditions and expand the communication distance, thereby leading to the advancement of the drone industry.

• Journal of Auto-vehicle Safety Association
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• v.16 no.2
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• pp.20-26
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• 2024

The delivery using drones has been attracting attention because it can innovatively reduce the delivery time from the time of order to completion of delivery compared to the current delivery system, and there have been pilot projects conducted for safe drone delivery. However, the current drone delivery system has the disadvantage of limiting the operational efficiency offered by fully autonomous delivery drones in that drones mainly deliver goods to pre-set landing sites or delivery bases, and the final delivery is still made by humans. In this paper, to overcome these limitations, we propose obstacle detection and landing site selection algorithm based on a vision sensor that enables safe drone landing at the delivery location of the product orderer, and experimentally prove the possibility of station-to-door delivery. The proposed algorithm forms a 3D map of point cloud based on simultaneous localization and mapping (SLAM) technology and presents a grid segmentation technique, allowing drones to stably find a landing site even in places without prior information. We aims to verify the performance of the proposed algorithm through streaming data received from the drone.

• Journal of the Semiconductor & Display Technology
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• v.17 no.3
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• pp.1-9
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• 2018

The drone has the restrictions on the controls, the battery and the surrounding environment in performing missions such as fire extinguishing. This restriction can improve the limitations that leave the leader can be monitored. The existing method of constructing the leader based on the GPS is highly dependent on the signal and is vulnerable to hardware defects. In this paper, we solve these problems with dynamic leaders decision. Drones can use their leader drones rather than remote controls. Information about the drones changes depending on the surrounding environment by replacing the leader with a dead battery or electing leader by the drones themselves without human intervention. This suggests that the leader monitors the community through a framework for continuing the drones collaboration and that the community can collaborate to overcome the limitations and continue the mission. The analysis of the proposed system through simulation experiments confirm that it has a better task performance. By using this system, it is possible to continue the mission and solve problems that are vulnerable to hardware defects.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.94-98
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• 2021

As the world's population grows, the food industry becomes increasingly important. Among them, agriculture is an industry that produces stocks of people all over the world, which is very important food industry. Despite the growing importance of agriculture, however, a large number of crops are lost every year due to pests and malnutrition. So, we propose a plant anomaly detection system for managing crops incorporating deep learning and drones with various possibilities. In this paper, we develop a system that analyzes images taken by drones and GPS of the drone's movement path and visually displays them on a map. Our system detects plant anomalies with 97% accuracy. The system is expected to enable efficient crop management at low cost.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.247-257
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• 2020

The Purpose of this study is to present effective Anti-Drone systems to protect national important facilities against drones that are illegally used by crime groups and terrorists with malicious intents. In order to accomplish the purpose of the study, technical and policy reports regarding Anti-Drone systems, open documents from manufacturers and various research papers are reviewed, and in-depth interviews with experts were conducted. Studies have shown that it is effective to overlay and mix different detection systems so that they can improve detection rates by supplementing each other's advantages and disadvantages, and that the means of incapacitation need to acquire flexibility by using both soft-kill and hard-kill methods in accordance with operational environment for the effective usage. In other words, the establishment of an illegal drone pre-management system, mixed and overlapping detection assets, determining appropriate countermeasures, and multiple distribution of means of incapacitation. The establishment of a protection system for important national facilities through the operation of overlapping and complex anti-drone systems is the most urgent task.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.578-589
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• 2019

The drones, developed for military use, have recently expanded a wide range of areas of use, including agriculture, industry, broadcasting utility, police, fire fighting and leisure. Drone, combined with IT technology, is further expanding its utilization and emerging as a key part of the fourth industry. Purpose: This study designs and implements drones that can be utilized in disaster prevention areas such as disaster prevention, preparedness and response. Method: This study was conducted by examining hardware drone specifications and developing a program suitable for the purpose of research based on the literature review. Result: In this study, we developed a drone that can be controlled remotely, investigated program plans for drone remote control, and developed a program that enables remote control broadcasting from drones. Conclusion: The drone could be used in the disaster area based on functions such as remote control and remote broadcasting.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.205-210
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• 2022

Drones, which have rapidly grown along with the 4th industrial revolution, spread over industries and also widely used for military purposes. In recent wars in Europe, drones are being evaluated as a game changer on the battlefield, and their importance for military use is being highlighted. The Republic of Korea Army also planned drone-bot systems including various drones suitable for echelons and missions of the military as future defense forces. The keyword of these drone-bot systems is autonomy by artificial intelligence. In addition, common use of operating platforms is required for the rapid development of various types of drones. In this paper, we propose software framework that applies diverse artificial intelligence technologies such as multi-agent system, cognitive architecture and knowledge-based context reasoning for mission autonomy and common use of military drones.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.93-104
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• 2023

Recently, the technology of drones is developing remarkably. The role of military drones is so great that they can cause serious damage to the enemy's important strategic assets without any damage to our allies in all battlefield environments (land, sea, air). However, the battleship combat management system currently operated by the Korean Navy is vulnerable to defense because there is no customized defense system against drones. As drones continue to develop, they are bound to pose a major threat to navy in the future. This paper proposes a way for the warfare software of naval combat management system sets a combat mode suitable for anti-drone battle, evaluates the threat priority in order to preemptively respond to drone threats and eliminate drone threats through automatic allocation of self-ship-mounted weapons and sensors, and through a test of the improved warfare software in a simulated environment, it was proved that the time to respond to the drone was improved by 62%.