• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_2
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• pp.1145-1153
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• 2023

This study presents the development of pointcloud data integration technology in construction sites via drone photogrammetry and MMS LiDAR. The integration of pointcloud data from drones and MMS technology can provide precise and accurate 3D digital maps of construction sites, which can benefit the development of smart construction and BIM. The advantages of using both drones and MMS technology for pointcloud data acquisition in construction sites are discussed, along with the limitations and challenges of using drone photogrammetry and MMS LiDAR for pointcloud data integration. The results of this study can contribute to the advancement of pointcloud data integration technology in construction sites and improve the efficiency and accuracy of construction projects.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.261-262
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• 2023

Drone is a suitable equipment for capturing images of cracks at construction sites based on its efficient mobility and high-resolution image acquisition capabilities. In this study, drone was used to acquire indoor construction sites framework images and deep learning technology was applied to detect cracks and measure width, and size. Finally, the usability of the process was verified based on the indoor crack monitoring system.

• Proceedings of KOSOMES biannual meeting
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• 2018.06a
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• pp.202-202
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• 2018

• Journal of Aerospace System Engineering
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• v.14 no.5
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• pp.18-25
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• 2020

This paper provides the basic data of low-altitude small drone management technology to solve the problem of drone's dysfunction that generally increases with the demand of the drone. Accordingly, various low-altitude small drone identification technology employed in many countries were investigated and analyzed. Herein, the research cases which have been developed to obtain diverse information such as the flight's plan, pilot's identity and contact number, and the flight's information such as the location and speed of small drones were mainly investigated. Furthermore, the list of the features of each case was analyzed. Moreover, the present paper suggests a drone identification system configuration which complements the problems of existing technologies and verifies the proposed system through a flight test.

• Journal of Advanced Navigation Technology
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• v.24 no.5
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• pp.393-407
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• 2020

In order to reduce the threat by illegal unmanned aerial vehicles, a tracking system based on sound was implemented. There are three main points to the drone acoustic tracking method. First, it scans the space through variable beam formation to find a sound source and records the sound using a microphone array. Second, it classifies it into a hidden Markov model (HMM) to find out whether the sound source exists or not, and finally, the sound source is In the case of a drone, a sound source recorded and stored as a tracking reference signal based on an adaptive beam pattern is used. The simulation was performed in both the ideal condition without background noise and interference sound and the non-ideal condition with background noise and interference sound, and evaluated the tracking performance of illegal drones. The drone tracking system designed the criteria for determining the presence or absence of a drone according to the improvement of the search distance performance according to the microphone array performance and the degree of sound pattern matching, and reflected in the design of the speech reading circuit.

• Journal of Advanced Navigation Technology
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• v.21 no.3
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• pp.272-278
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• 2017

In order to meet performance requirements specified by the ICAO in drone operation, a system that provides augmentation information such as SBAS is needed. However, the operating range of the drone is limited in situation where the drone can not received the SBAS message continuously. In this paper, we propose a system to transmit SBAS augmentation message using a separate communication channel assuming the SBAS satellite signal to the drone has been shielded. We implemented the proposed system and verified its performance in the static environment. The DGPS positioning results showed that the accuracy difference is about 10cm, which means the accuracy performance was very similar. In addition, the protection level calculated by the system also shows the difference within 2m from the value calculated by the airborne receiver.

• Explosives and Blasting
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• v.38 no.3
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• pp.1-14
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• 2020

Stereophotogrammetry can be used for accurate and fast investigation of over-break or under-break which may form during the blasting of underground space. When integrated with small unmanned aerial vehicles(UAVs) or drones, stereophotogrammetry can be performed much more efficiently. However, since previous research are mostly focused on surface environments, underground applications of drone-based stereophotogrammetry are limited and rare. In order to expand the use of drone-based stereophotogrammetry in underground environments, this study investigated a rock surface of a underground mine through drone-based stereophotogrammetry. The accuracy of the investigation was evaluated and analyzed, which proved the method to be accurate in underground environments. Also, recommendations were proposed for the image acquisition and matching conditions for accurate and efficient application of drone-based stereophotogrammetry in underground environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.355-358
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• 2016

Recently, As the interest of the drone has increased the fields such as broadcasting, disaster site and leisure which uses the drone has been constantly expanded. However, an invasion of a person's privacy and a threat of hacking attack also have increased as population of drone. High-resolution cameras mounted on drones can take a photo or real-time video anytime and anywhere. It causes the invasion of privacy from private houses, buildings, and hotels. In this paper, we perform a security vulnerability assessment tests on the camera's from common commercial drones and we propose the countermeasures to protect the drones against unauthorized attacker who attempts to access the drone's camera from internal or external. Through this research, we expect the Aviation Act and legislation accept the concept of security and provide the polices such as drones equipped with security devices from the production stage to promote drone industry.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.2
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• pp.159-162
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• 2017

Along with the popular use of commercial drones, there are increased concerns on the possible threats from drones intruding into secured areas. The difficulty of drone detection is attributed to its stealthy operation flying at low altitude with low level signature. Consequently, the anti-drone technique has been of major research topic in recent years and among others, the radar detection is considered as the most promising technique. However, the use of conventional radar detection may not be effective due to the low level radar cross sections of the commercial drones. In this paper, ISAR technique has been employed to implement drone detection in urban area. To this purpose, a pulsed radar system is set up on the ground to track flying drones and the corresponding ISAR images are produced by coherent processing.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.33-38
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• 2020

This paper proposes a technique for counting construction materials by analyzing an image acquired by a Drone. The proposed technique use drone log which includes drone and camera information, RCNN for predicting construction material type, dummy area and Photogrammetry for counting the number of construction material. The existing research has large error ranges for predicting construction material detection and material dummy area, because of a lack of training data. To reduce the error ranges and improve prediction stability, this paper increases the training data with a method of data augmentation, but only uses rotated training data for data augmentation to prevent overfitting of the training model. For the quantity calculation, we use a drone log containing drones and camera information such as Yaw and FOV, RCNN model to find the pile of building materials in the image and to predict the type. And we synthesize all the information and apply it to the formula suggested in the paper to calculate the actual quantity of material pile. The superiority of the proposed method is demonstrated through experiments.