• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.1-8
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• 2021

In this paper, we propose the construction of an IOT that monitors foresters' physical abnormalities in real time, performs emergency measures, and provides alarms for natural disasters or heatstroke such as a nearby forest fire or landslide. Nodes provided to foresters include 6-axis sensors, temperature sensors, GPS, and LoRa, and transmit the measured data to the network server through the gateway using LoRa communication. The network server uses 6-axis sensor data to determine whether or not a forester has any signs of abnormal body, and performs emergency measures by tracking GPS location. After analyzing the temperature data, it provides an alarm when there is a possibility of heat stroke or when a forest fire or landslide occurs in the vicinity. In this paper, it was confirmed that the real-time detection of physical abnormalities of foresters and the establishment of disaster early warning IOT is possible by analyzing the data obtained by constructing a node and a gateway and constructing a network server.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.107-114
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• 2022

In this paper, proposes a delivery robot that can be autonomous driving learning. The proposed robot is designed to be used in park-type apartments without ground parking facilities. Compared to the existing apartments with complex ground and underground routes, park-type apartments have a standardized movement path, allowing the robot to run stably, making it suitable for students' initial education environment. The delivery robot is configured to enable delivery of parcels through machine learning technology for route learning and autonomous driving using cameras and LiDAR sensors. In addition, the control MCU was designed by separating it into three parts to enable learning by level, and it was confirmed that it can be used as a delivery robot for learning through operation tests such as autonomous driving and obstacle recognition. In the future, we plan to develop it into an educational delivery robot for various delivery services by linking with the precision indoor location information recognition technology and the public technology platform of the apartment.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.497-497
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• 2023

정수장에서 소독 및 여과 처리가 완료된 깨끗한 물은 배급수시설로 전달되나, 실제로 관의 노후화, 갑작스러운 유향 변동, 특정 구역의 관 내 정체 시간에 따른 Water Age 상승 등 여러 요인으로 인해 실제 수용가에는 안전하지 않은 용수가 공급될 가능성이 있으며, 이에 따라 적절한 위치에서 지속적인 감시를 통한 조기 발견 및 조치가 필요하다. 상수도 시설기준(2010)에 배수시설의 주요 지점 혹은 관 말단 등 필요에 따라 적절한 위치에 수질 계측기를 설치할 수 있도록 제시되어 있으나, 계측기 설치 위치나 개수에 대한 기준이 모호한 실정이다. 모든 구역에 수질계측기를 설치하여 감시하는 것이 이상적이지만, 현실적으로는 지자체 환경 및 경제적인 한계가 있어 주요 위치에 설치하는 것이 바람직하다. 본 연구에서는 대표적인 수리해석 모형인 EPANET을 사용하여 대상 관망의 노후도, 유속, 유향변동 등의 영향인자를 바탕으로 수질사고가 발생할 확률이 높은 관을 위험관으로 선정하고, 선정된 위험관을 대상으로 최단 경로와 Cost를 산출할 수 있는 Floyd Warshall Algorithm을 이용하여 각 Node(수용가)간 물이 이동할 때의 최소 도달시간과 경로를 파악하였다. 또한, 시간 서비스 수준(Level of T hour Serivice)의 개념을 도입하여 위험관으로부터 특정시간 이내에 흐름이 도달하는 Node를 파악한 뒤, 그 중 가장 많은 피해를 발생시킬 수 있는 위험관을 수질계측위치 지점으로 선정하였다. 제시된 수질사고 발생위험이 높은 위험관을 대상으로 수질계측 위치를 선정하는 방법이 전체 관망 네트워크를 대상으로 수질계측 위치를 판단하는 방법보다 결과 신뢰도 측면에서 더욱 효과적이고 효율적인 방법으로 사료된다.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.250-256
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• 2009

This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.

• Journal of Space Technology and Applications
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• v.3 no.1
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• pp.58-71
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• 2023

This paper describes a navigation system design for horizontal position estimation using inertial measurement sensors and celestial navigation. In space, stars are widely spread objects in the celestial sphere and have been used mainly to obtain attitude information through star observation. However, it is also possible to obtain information about the horizontal position with the altitude of the star. It is called celestial navigation which is the same principle that former navigators used to locate themselves while sailing on the sea. In particular, in deep space where GPS is not available, it is important to obtain information on the location by making use of stars that are relatively easy to observe. Therefore, we introduce a navigation system that can estimate horizontal position and design two types of systems, loosely coupled and tightly coupled depending on how the measurements are utilized. It is intended to help in the future design of navigation system using celestial navigation by simulation studies that not only verify whether the system correctly estimates horizontal position but also comparing the performance of loosely and tightly coupled methods.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.157-165
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• 2009

In this paper, we propose a distributed model that recognize ADLs of human can be occurred in daily living places. We collect and analyze user's environmental, location or activity information by simple sensor attached home devices or utensils. Based on these information, we provide a lifecare services by inferring the user's life pattern and health condition. But in order to provide a lifecare services well-refined activity recognition data are required and without enough inferred information it is very hard to build an ADL activity recognition model for high-level situation awareness. The sequence that generated by sensors are very helpful to infer the activities so we utilize the sequence to analyze an activity pattern and propose a distributed linear time inference algorithm. This algorithm is appropriate to recognize activities in small area like home, office or hospital. For performance evaluation, we test with an open data from MIT Media Lab and the recognition result shows over 75% accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.69-74
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• 2022

Even after the drunk driving law was revised through the Yoon Chang-ho Act in 2019, the proportion of habitual offenders among all drunk drivers in 2021 was 4.7%, up 0.5% from 2018. In addition, drunk driving is not easily stopped due to the addiction of alcohol, and there is a high probability of recidivism in accidents as it is often driven again. Therefore, in this paper, to prevent this, when alcohol is measured using its own sensor rather than a manual police measure, the vehicle stops and related data such as the current location and time are automatically saved. Since it is not possible to develop directly on the car, this system was developed by converging various technologies and sensors such as Arduino board, Firebase, and GPS based on the IoT environment in consideration of the simulation environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1653-1659
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• 2022

Virtual reality content provides users with a high sense of immersion by using HMD devices. However, while wearing the HMD device, it is difficult to determine the user's location or distance from obstacles, resulting in injuries due to physical collisions. In this paper, we propose a reminder module to prevent accidents by notifying the risk of collision with obstacles while wearing the HMD device. The proposed module receives the user's state from the acceleration and gyro sensor and determines the motion that is likely to cause a collision. If there is an obstacle in the expected collision range, a buzzer sounds to the wearer. As a result of the experiment, the accuracy of obstacle detection in the state of wearing the HMD was 86.6% in the 1st stage and 83.3% in the 2nd stage, confirming the performance of the accident prevention reminder.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.291-295
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• 2022

This paper deal with the advanced thchnology of water supply line breakege detection system in singsan green city. the technology apply for construction eco oriented high-tech city to merge residant, industial, tour reasure parts for songsan green city furture direction achivement and response for a life style change of people in the city. Breakege detection system consist of smart prevention seat, pipeline breakege detection sensor, analysis software, server. etc.. Central control unit sent the data to hwa sung city water supply office by WCDMA in SKY. the data are states about water supply pipeline, Location.etc. This system maintain the long term life cycle of water supply plpeline by the prevention the leakege event through ackonwledge information of evnet occurrence locaion. and used to realtime sense method about demage information of the pipeline and prevent to brekege facilities during excavation work.