• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1890-1897
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• 2021

People counting is an important technology to provide application services such as smart home, smart building, smart car, etc. Due to the social distancing of COVID-19, the people counting technology attracted public attention. People counting system can be implemented in various ways such as camera, sensor, wireless, etc. according to service requirements. People counting system using WiFi AP uses WiFi CSI data that reflects multipath information. This technology is an effective solution implementing indoor with low cost. The conventional WiFi CSI-based people counting technologies have low accuracy that obstructs the high quality service. This paper proposes a deep learning people counting system based on WiFi CSI data. Data preprocessing using auto-encoder, data augmentation that transform WiFi CSI data, and a proposed deep learning model improve the accuracy of people counting. In the experimental result, the proposed approach shows 89.29% accuracy in 6 subjects.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.55-69
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• 2017

Recently, the IoT (Internet of Things) environment is being developed rapidly through network which is linked to intellectual objects. Through the IoT, it is possible for human to intercommunicate with objects and objects to objects. Also, the IoT provides artificial intelligent service mixed with knowledge of situational awareness. One of the industries based on the IoT is a car industry. Nowadays, a self-driving vehicle which is not only fuel-efficient, smooth for traffic, but also puts top priority on eventual safety for humans became the most important conversation topic. Since several years ago, a research on the recognition of the surrounding environment for self-driving vehicles using sensors, lidar, camera, and radar techniques has been progressed actively. Currently, based on the WAVE (Wireless Access in Vehicular Environment), the research is being boosted by forming networking between vehicles, vehicle and infrastructures. In this paper, a research on the recognition of a traffic signs on highway was processed as a part of the awareness of the surrounding environment for self-driving vehicles. Through the traffic signs which have features of fixed standard and installation location, we provided a learning theory and a corresponding results of experiment about the way that a vehicle is aware of traffic signs and additional informations on it.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.263-267
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• 2015

current mine detector can't division the section if it is conducted and it needs too much labor force and time. in addition to, if the user don't move the head of sensor in regular speed or move it too fast, it is hard to detect a mine exactly. according to this, to improve the problem using one direction ultrasonic wave sensing signal, that is made up of human body antenna part, main micro processor unit part, smart glasses part, body equipped LCD monitor part, wireless data transmit part, belt type power supply part, black box type camera, Security Communication headset. the user can equip this at head, body, arm, waist and leg in removable type. so it is able to detect the powder in a 360-degree on(under) the ground whether it is metal or nonmetal and it can express the 2D or 3D film about distance, form and material of the mine. so the battle combats can avoid the mine and move fast. also, through the portable battery and twin self power supply system of the power supply part, combat troops can fight without extra recharge and we can monitoring the battle situation of distant place at the command center server on real-time. and then, it makes able to sharing the information of battle among battle combats one on one. as a result, the purpose of this study is researching a smart wearable mine detector which can establish a smart battle system as if the commander is in the site of the battle.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.396-401
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• 2016

Owing to developments in the internet of things, many products have developed and various researches have processed. Smart home systems in Internet of things area are receiving attention from many people than the other areas. Autonomous mobile robots perform various parts in many industries. In this paper, a smart housekeeping robot was implemented using internet of things and an autonomous mobile robot. In order to make a smart housekeeping robot, Raspberry Pi, wireless USB camera, and uBrain robot of Huins Corp. is used. To control the robot, cell-phone connected with IP of Raspberry Pi, and then Raspberry Pi connected with uBrain robot using Bluetooth. a smart housekeeping robot was controlled using commands of a cell-phone application. If some user wants to move a robot automatically, we implemented that a robot can be chosen an autonomous driving mode from the user. In addition, we checked a realtime video using a cell-phone and computer. This smart housekeeping robot can help user check their own homes in real time.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.11-18
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• 2010

In this paper, it introduced the device that was fabricated for monitoring sleeping positions of infants with 3-axis accelerometer. Sleep monitoring studies has been usually conducted two ways. To monitor sleeping posture by installing a camera and then recording of sleep in the sleeping room continuously is the first one. The other one is monitoring pressure sensor's results data for sleeping. Those two ways' benefits are that are able to get relatively accurate sleeping posture data but, there are many disadvantages like constraints of spaces and places, the installation of sensors or cameras, and high cost. In addition, it has a lot of problems that difficult to solve. For babies, it's not easy to apply, as well as uncomfortable. The proposed method uses a 3-axis accelerometer's X axis, Y axis, Z axis position output values in order to recognize the bad ground sleeping position that use of the buzzer alarm. This method uses a 3-axis acceleration sensor to measure the data and transmit sleeping posture using Bluetooth wireless in real time monitoring. The data is helpful for prevention safety hazard such as choked themselves when they slept back side on.

• Journal of Korea Water Resources Association
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• v.44 no.5
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• pp.377-388
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• 2011

Surface Image Velocimetry (SIV) is a recently-developed discharge measurement instrument. It uses image processing techniques to measure the water surface velocity and estimate water discharge with given cross section. The present study aims to implement a FSIV (Fixed-type Surface Image Velocimetry) at Soojeon Bridge in the Dalcheon. The hardware system consists of two digital cameras, a computer, and a pressure-type water stage gauge. The images taken with the hardware system are sent to a server computer via a wireless internet, and analyzed with a image processing software (SIV software). The estimated discharges were compared with the observed discharges through Goesan dam spillway and index velocity method using ADVM. The computed results showed a good agreement with the observed one, except for the night time. The results compared with discharges through Goesan dam spillway reached around 5~10% in the case of discharge over 30 m3/s, and the results compared with discharges through index velocity method using ADVM reached around 5% in the case of discharge over 200 $m^3/s$. Considering the low cost of the system and the visual inspection of the site situation with the images, the SIV would be fairly good way to measure water discharge in real time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.1960-1972
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• 2006

In this thesis, GPS and the electronic mapping were used to realize such a system by recognizing license plate numbers and identifying the location of objects that move at synchronous times with simulated movement in the electronic map. As well, throughout the study, a camera attached to a PDA, one of the mobile devices, automatically recognized and confirmed acquired license plate numbers from the front and back of each cu. Using this mobile technique in a wireless network searches for specific plate numbers and information about the location of the car is transmitted to a remote sewer. The use of such a GPS-based system allows for the measurement of topography and the effective acquisition of a car's location. The information is then transmitted to a central controlling center and stored as text to be reproduced later in the form of diagrams. Getting positional information through GPS and using image-processing with a PDA makes it possible to estimate the correct information of a car's location and to transmit the specific information of the car to a control center simultaneously, so that the center will get information such as type of the cu, possibility of the defects that a car might have, and possibly to offer help with those functions. Such information can establish a mobile system that can recognize and accurately trace the location of cars.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.595-605
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• 2006

In this thesis, GPS and the electronic mapping were used to realize such a system by recognizing license plate numbers and identifying the location of objects that move at synchronous times with simulated movement in the electronic map. As well, throughout the study, a camera attached to a PDA, one of the mobile devices, automatically recognized and confirmed acquired license plate numbers from the front and back of each car. Using this mobile technique in a wireless network, searches for specific plate numbers and information about the location of the car is transmitted to a remote server. The use of such a GPS-based system allows for the measurement of topography and the effective acquisition of a car's location. The information is then transmitted to a central controlling center and stored as text to be reproduced later in the form of diagrams. Getting positional information through GPS and using image-processing with a PDA makes it possible to estimate the correct information of a car's location and to transmit the specific information of the car to a control center simultaneously, so that the center will get information such as type of the car, possibility of the defects that a car might have, and possibly to offer help with those functions. Such information can establish a mobile system that can recognize and accurately trace the location of cars.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.51-57
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• 2019

In this paper, we analyzed the performance of IoT based smart wearable mine detection device. There are various mine detection methods currently used by the military. Still, in the general field, mine detection is performed by visual detection, probe detection, detector detection, and other detection methods. The detection method by the detector is using a GPR sensor on the detector, which is possible to detect metals, but it is difficult to identify non-metals. It is hard to distinguish whether the area where the detection was performed or not. Also, there is a problem that a lot of human resources and time are wasted, and if the user does not move the sensor at a constant speed or moves too fast, it is difficult to detect landmines accurately. Therefore, we studied the smart wearable mine detection device composed of human body antenna, main microprocessor, smart glasses, body-mounted LCD monitor, wireless data transmission, belt type power supply, black box camera, which is to improve the problem of the error of mine detection using unidirectional ultrasonic sensing signal. Based on the results of this study, we will conduct an experiment to confirm the possibility of detecting underground mines based on the Internet of Things (IoT). This paper consists of an introduction, experimental environment composition, simulation analysis, and conclusion. Introduction introduces the research contents such as mines, mine detectors, and research progress. It consists of large anti-personnel mine, M16A1 fragmented anti-mine, M15 and M19 antitank mines, plastic bottles similar to mines and aluminum cans. Simulation analysis is conducted by using MATLAB to analyze the mine detection device implementation performance, generating and transmitting IoT signals, and analyzing each received signal to verify the detection performance of landmines. Then we will measure the performance through the simulation of IoT-based mine detection algorithm so that we will prove the possibility of IoT-based detection landmine.

• 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.