• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.9-14
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• 2019

In modern society drones are actively utilized in the fields of security, defense, agriculture, communication and so on. Smart technology and artificial intelligence software have been developed with convergence, and the field of use is expected to expand further. On the point of the excellent performance of drones one of the essential technologies is the wireless communication that make the ground facility receive the video streaming obtained by the drones in the air. In the research the concept of communication region is proposed to cover the both the low altitude region for Wi-Fi communication and the high altitude region for LTE communication for the sake of video transmission. Also the hybrid communication structure is designed along the proposed concept and the proposed system is implemented as a communication system in the small size which can be mounted in a small size of drone. It is confirmed that the proposed system contains the effectiveness by showing the ability to successfully transmit HD video streaming in the range of 500 meters and the transfer time between two different communication systems is measured in 200msec by the experiments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.161-167
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• 2019

Recently, demand forecasting techniques have been actively studied due to interest in stable power supply with surging power demand, and increase in spread of smart meters that enable real-time power measurement. In this study, we proceeded the deep learning prediction model experiments which learns actual measured power usage data of home and outputs the forecasting result. And we proceeded pre-processing with moving average method. The predicted value made by the model is evaluated with the actual measured data. Through this forecasting, it is possible to lower the power supply reserve ratio and reduce the waste of the unused power. In this paper, we conducted experiments on three types of networks: Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short Term Memory (LSTM) and we evaluate the results of each scheme. Evaluation is conducted with following method: MSE(Mean Squared Error) method and MAE(Mean Absolute Error).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.25-30
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• 2024

Smart City, a key application area of the AIoT (Artificial Intelligence of Things), provides various services in safety, security, and healthcare sectors through location tracking and location-based services. an IPS (Indoor Positioning System) is required to implement location-based services, and wireless communication technologies such as WiFi, UWB (Ultra-wideband), and BLE (Bluetooth Low Energy) are being applied. BLE, which enables data transmission and reception with low power consumption, can be applied to various IoT devices such as sensors and beacons at a low cost, making it one of the most suitable wireless communication technologies for indoor positioning. BLE utilizes the RSSI (Received Signal Strength Indicator) to estimate the distance, but due to the influence of multipath fading, which causes variations in signal strength, it results in an error of several meters. In this paper, we conducted research on a path loss model that can be applied to BLE IPS for proximity services, and confirmed that optimizing the free space propagation loss coefficient can reduce the distance error between the Tx and Rx devices.

• Journal of the Korean Institute of Gas
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• v.28 no.1
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• pp.53-58
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• 2024

Due to the development of industry and improvement of living standards, the amount of natural gas used in the world is constantly increasing, and related industrial facilities such as power plants, storage facilities, and supply pipelines are constantly increasing. Natural gas is a convenient and clean fuel that does not pollute the environment, but in the event of an accident due to leakage, it can cause human casualties, large-scale property damage, and negative effects on the global warming effect. In addition to the severe penalties under the Severe Disaster Punishment Act, it is necessary to ensure safety. Therefore, by applying the principle of laser-based absorption spectroscopy, we developed a long-range portable methane leakage gas detection system that can detect the concentration of methane leaking from a distance of up to 30 meters and verified its effectiveness.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.118-131
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• 2012

The existing electronic tagging system traces the location of a sex offender through communicating with GPS satellites and mobile phone base stations in order to prevent repeated crimes. However, the GPS satellite communication method does not work well in the interiors of downtown buildings or on the subways where it is difficult to receive satellite signals. In such cases, the location can be traced through communication with mobile phone base stations. But the distance between mobile phone base stations is several hundred meters, and as a result the margin of error for location tracing can be maximum of 2km in accuracy reduction. Take for example, if a kindergarten is located on the 2nd floor and a coffee shop and the sex offender are located on the 3rd floor in a 5-story building that is downtown, the existing electronic tagging system cannot trace the location of the sex offender as the GPS satellite communication does not work in the interior of the building and the exact floor that the sex offender is located on cannot be recognized through communication with mobile phone base stations. This occurrence is a big problem for the existing electronic tagging system, which is based on position recognition. Therefore, this study suggests a smart electronic tagging system that can monitor sex offenders by using a Ubiquitous Sensor Network in such extreme situations where position recognition is not possible.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.172-178
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• 2022

In this paper, water meter AMR(automatic meter reading), one of the core technologies of smart water grid, using LoRa IoT network is studied. The main content of the research is to develop the network system and show the test results that one PC server receives the readings of water meters from multiple households through LoRa communication and stores them in the database, and at the same time sends the data to the web server database through internet. The system also allows users to monitor the meter readings using their smartphones. The hardware and firmware of the main board of the digital water meter are developed. For a PC server program, MDMS(meter data management system) is developed using Visual C#. The app program running on the user's smartphone is also developed using Android Studio. By connecting each developed parts, the total network system is mounted on a flow test bench in the laboratory and tested. For the fields test, 5 places around the university are selected and the transmission distances are tested. The test result show that the developed system can be applied into the real field. The developed system can be expanded to various social safety nets such as monitoring the living alone or elderly with dementia.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.105-116
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• 2020

The purpose of this study is to progress the limitations and disadvantages of existing safety clothing by applying high technology to current safety clothing that is produced and distributed only with fluorescent fabrics and retroreflective materials. Therefore, the industrial suspender-type safety belt and engineering technology are introduced, designed, and fabricated to help save a life in an emergency. First, the suspender-type safety belt to be developed is designed to emit light by LED attached to the film, and the body of the belt-wearer is recognized from a distance through retroreflection from the flashing LED. It aims to support people's safety by preventing accidents during roadside work, rescue activities, and sports activities at night. Second, with the development of advanced devices when the user is in an unconscious state due to distress or falls into an unconscious state due to distress or accident, the tilt sensor of the control unit attached to the belt automatically detects the angle of the human body and generates light and sound. It is intended to further enhance the utilization by mounting a sensing and signaling device that generates a distress signal and shaping it in the form of a belt attached to a vest that can be easily detached from the outside of the garment. When the wearer falls due to an accident, the tilt sensor of this belt detects the angle change and then the controller generates a high-frequency sound and repeated LED blinking signals at the same time. In the case of conventional safety vests, it is almost impossible to detect that the person is wearing a vest when there is no ambient light, but in case of the safety belts in this study, the sound and light signals of the safety belt enable us to find the wearer within 100 meters even when there is no ambient light.