• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.457-462
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• 2022

Recently, a variety of cultural life using drones as an entertainment tool has been created, and in order to realize this, more and more users are using drones with good performance enough to invade the no-flight zone. Drones for satisfying entertainment activities must have long flight times and be able to fly long distances, which can often cause great damage by invading no-flight zones or causing unwanted flight crashes. In this study, in order to solve this problem, a no-flight zone is set with GCS(Ground Control System), and when flying at a critical speed of 10km/h or less, the drone is safely operated by not entering the critical distance 10m away from the no-flight zone, and the critical speed A method was proposed to prevent the drone from entering the no-flight zone by allowing the drone to self-drop by GCS control when it flies beyond the threshold and enters the critical distance. As a result of a total of 44 repeated experiments in a specific experimental area with the proposed method, the drone safely self-dropped except for the case where it crossed the restricted area once or twice. It was found to be an appropriate way to prevent this.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.84-90
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• 2019

Applications of unmanned aerial vehicles (UAVs) in the military environment have become popular because they require minimum human contribution and can avoid accidents during missions. UAVs are employed in various missions such as reconnaissance, observation, aggression, and protection. Consequently, counter-measures, known as anti-drone technologies, have been developed as well. In order to protect against threats from anti-drone technologies and enhance the survivability of UAVs, this study proposes an evasive measure. The proposed bio-inspired evasive maneuver of a UAV mimics a dragonfly's irregular flight. The unpredictable UAV movement is able to confuse enemies and avoid threats, thereby enhancing the UAV's survivability. The proposed system has been implemented on a commercial UAV platform (AR Drone 2.0) and tested in a real environment. The experiment results demonstrate that the proposed flight pattern has larger displacement values compared to a regular flight maneuver, thus making the UAV's position is difficult to predict.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1043-1048
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• 2017

Since year 2016, in Korea, the police department started to use drones to patrol violated vehicles on the highway area. They monitor vehicle drivers who use side ways on the highway during traffic congested hours of the season, drunken drivers, or violent drivers. They use the 'Spot Mobility' method which floats the drones for 30 minute period. However, this method is inefficient since it requires manually charging batteries, gathering data, and operate drones with many numbers of policeman. Therefore, in this paper, for the efficient patrol in this purpose, I have suggested an effectively manageable network system consists of many drones as the wireless network nodes and with small numbers of policeman in a wide highway area. To accomplish this, the two topologies of effective drone patrol network systems are designed and simulated in OPNET simulator for performance evaluation.

• Convergence Security Journal
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• v.23 no.3
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• pp.65-71
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• 2023

The importance of combat drones has been highlighted through the recent outbreak of the Russia-Ukraine war. The combat drones play a significant role as a a game changer that alters the conventional wisdom of traditional warfare. Many pundits expect the role of combat swarm drones would be more crucial in the future warfare. In this regard, this paper aims to analyze the development of artificial intelligence-enabled combat swarm drones. To transform the human-operated swarm drones into fully autonomous weaponry system our suggestions are as follows. Developments of (1) AI algorithms for optimized swarm drone operations, (2) decentralized command and control system, (3) inter-drones' mission analysis and allocation technology, (4) enhanced drone communication security and (5) set up of ethical guideline for the autonomous system. Specifically, we suggest the development of AI algorithms for drone collision avoidance and moving target attacks. Also, in order to adjust rapidly changing military environment, decentralized command and control system and mission analysis allocation technology are necessary. Lastly, cutting-edging secure communication technology and concrete ethical guidelines are essential for future AI-enabled combat swarm drones.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.431-437
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• 2024

Drones in the contemporary landscape have transcended their initial public utility, expanding into various industries and making significant inroads into the private sector. The majority of commercially available drones are presently equipped with GPS receivers to relay location signals from artificial satellites, aiming to inform users about the drone's whereabouts. However, a notable drawback arises from the considerable distance over which these location signals travel, resulting in a weakened signal intensity. This limitation introduces vulnerabilities, allowing for the possibility of location manipulation and jamming attacks if the drone receives a stronger signal than the intended location signal from satellites. Thus, this paper focuses on the safety assessment of drones relying on GPS-based location acquisition and addresses potential vulnerabilities in wireless communication scenarios. Targeting commercial drones, the paper analyzes and empirically demonstrates the feasibility of GPS spoofing attacks. The outcomes of this study are anticipated to serve as foundational experiments for conducting more realistic vulnerability analysis and safety evaluations.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.923-928
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• 2016

The various technologies related to the monitoring human health in real-time for the emergency situations are developing these days. Mostly the human pulse is used for measuring as the vital signs so far, but the EEG became a major research trend now. However, there are some problems measuring and sending EEG signals of all the people walking down the street to the dedicated server. Especially, there are some restrictions for collecting and sending EEG signals in 2-dimensional space in real-time. Therefore, I suggests an efficient network model using 3-dimensional space of drones to avoid the restrictions. The models are designed, simulated, and evaluated with the Opnet simulator.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.136-145
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• 2018

The disaster monitoring technique by combination of the measurement method and the fine precision of the sensor collecting the satellite-based information that can determine the displacement space is available in a variety of diagnostic information and the GIS/GNSS by first sensor it is being requested from them. Be large and that the facility is operated nationally distributed torsional displacement of the terrain and facilities caused by such natural disasters progress of various environmental factors and the surroundings. To diagnose this spatial information, which contains the various sensors and instruments tracks the precise fine displacement of the main construction structures and the first reference in the Geospatial or more three-dimensional detailed available map and location information using the installed or the like bridges and tunnels produced to a USN/IoT change at any time, by combining the various positioning analysis of mm-class for the facility main area observed is required to constantly in the real time information of the USN/IoT environment sensor, and to utilize this as a precise fine positioning information by UAV/Drone to the precise fine displacement of the semi-permanent infrastructures. It managed to be efficient management by use of new technologies, analyzing the results presented to a method capable of real-time monitoring for a large structure or facility to construction disaster prevention.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1379-1386
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• 2018

Conventional underwater cameras used in fish farms can only shoot limited areas and are vulnerable to underwater contamination. There is also a problem with contaminated farms as surplus residues are deposited as a result of feed supply to farms' nets. This paper proposes underwater drones for underwater monitoring of fish farms and cleaning nets. If underwater drones are used for management of fish farms, underwater imaging, monitoring and cleaning of fish farms' nets can be possible. By using this technology, data can be collected by detecting changes in the environment of a fish farm and responding to changes that occur within a fish farm based on the data. In addition, the establishment of an integrated control system will enable to build efficient and stable smart farms.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.405-412
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• 2023

With the development of drone and ICT convergence technology, the use of underwater drones such as leisure underwater drones such as underwater exploration for fishing and industrial drones such as bridge piers is increasing. Existing motor controllers are suitable for aerial drones and these can increase the completeness of underwater drones and their reliability in motor control by developing BLDC motor controllers dedicated to underwater drones. By developing a battery management system (BMS) exclusively for underwater drones, battery stability was ensured by checking the state of charge, checking the state of discharge, adjusting cell balancing, and implementing high/voltage protection functions.