• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.669-670
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• 2020

현재 4차 산업이 진행됨으로써 대부분의 사물들이 자율화 기능이 더해지는 시대가 오고 있다. 자율화 기술이 발전됨으로써 모든 사람들은 삶을 살아가면서 스스로 문제를 해결해 나갈수 있으며 기존의 생활속도보다 빨라지는 것을 느낄수 있을 것이다. 그래서 마트에서도 쇼핑을하면서 소비자들이 어떻게 쇼핑을 할 때 현재의 수준보다 쇼핑의 질이 높아 질지 고안해보았다. 본 과제물은 소비자들이 쇼핑을할 때 보다 편리하게 일을 처리할수도록 스마트 기능을 카트와 카운터에 추가하였다. 카트에 디스플레이와 바코드 스캐너를 부착함으로써 검색을 통해 소비자들이 원하는 물품의 가격, 위치등의 정보를 알아 낼 수 있고 현재 카트에 담긴 물품의 총 가격을 알 수 있다. 또한, 쇼핑을 마치고 계산을할 때 계산 대기줄이 길어지는 불편함을 해소하기위해 자동계산 기능이 있다. 쇼핑을 마친 소비자가 카트를 카운터로 끌고가면 카트에 저장되어 있는 쇼핑정보가 카운터의 디스플레이에 표시되고 카트와 카운터의 정보가 일치한다면 소비자가 카트에 요금을 충전해 스스로 계산을 수행할수 있다. 이런 자동화, 스마트 기능들은 소비자들의 편리함과 시간을 단축시킬수 있을 것이다.

• Journal of Wetlands Research
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• v.22 no.4
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• pp.312-320
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• 2020

Various LIDs with natural water circulation function are applied to reduce urban environmental problems and environmental impact of development projects. However, excessive Infiltration and evaporation of LID facilities dry the LID internal soil, thus reducing plant and microbial activity and reducing environmental re duction ability. The purpose of this study was to develop a real-time measurement system with complex sensors to derive the management plan of LID facilities. The test of measurable sensors and Internet of Things (IoT) application was conducted in artificial wetlands shaped in acrylic boxes. The applied sensors were intended to be built at a low cost considering the distributed LID and were based on Arduino and Raspberry Pi, which are relatively inexpensive and commercialized. In addition, the goal was to develop complex sensor measurements to analyze the current state o f LID facilities and the effects of maintenance and abnormal weather conditions. Sensors are required to measure wind direction, wind speed, rainfall, carbon dioxide, Micro-dust, temperature and humidity, acidity, and location information in real time. Data collection devices, storage server programs, and operation programs for PC and mobile devices were developed to collect, transmit and check the results of measured data from applied sensors. The measurements obtained through each sensor are passed through the Wifi module to the management server and stored on the database server in real time. Analysis of the four-month measurement result values conducted in this study confirmed the stability and applicability of ICT technology application to LID facilities. Real-time measured values are found to be able to utilize big data to evaluate the functions of LID facilities and derive maintenance measures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.563-569
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• 2018

This paper is on the implementation of a system for automatically monitoring window farm hydroponics based on Arduino (utilizing Arduino's open source code) emerging as the icon of the Fourth Industrial Revolution. A window farm, which means window-type hydroponics, is offered as an alternative to fulfill the desires of people who want to grow plants aside from the busy daily life in the city. The system proposed in this paper was developed to automatically monitor a window farm hydroponics cultivation environment using the Arduino UNO board, a four-charmel motor shield, temperature and humidity sensors, illumination sensors, and a real-time clock module. Modules for hydroponics have been developed in various forms, but power consumption is high because most of them use general power and motors. Since it is not a system that is monitored automatically, there is a disadvantage in that an administrator always has to manage its operational state. The system is equipped with a water supply that is most suitable for a plant growth environment by utilizing temperature, humidity, and light sensors, which function as Internet of Things sensors. In addition, the real-time clock module can be used to provide a more appropriate water supply. The system was implemented with sketch code in a Linux environment using Raspberry Pi 3 and Arduino UNO.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1123-1132
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• 2018

In this paper, we design and implement a public bicycle sharing system based on smart phone application capable of distributing access codes via internet connection. When smartphone user uses the application to request a bicycle unlock code, server receives the request and sends an encrypted code, which is used to unlock the bicycle at the station and the same code is used to return the bicycle. The station's hardware prototypes were built on top of Internet devices such as raspberry pi, arduino, keypad, and motor driver, and smartphone application basically includes shared bike rental and return functionality. It also includes an additional feature of reservation for a certain time period. We tested the implemented system, and found that it is efficient because it shows the average of 3-4 seconds delay. The system can be implemented to manage multiple bikes with a single control box, and as the user can use a smartphone application, this makes the system more cost effective.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.163-169
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• 2020

Recently, research on automation and unmanned operation of machines in the industrial field has been conducted with the advent of AI, Big data, and the IoT, which are the core technologies of the Fourth Industrial Revolution. The machines for these automation processes are controlled based on the data collected from the sensors attached to them, and further, the processes are managed. Conventionally, the abnormalities of sensors are periodically checked and managed. However, due to various environmental factors and situations in the industrial field, there are cases where the inspection due to the failure is not missed or failures are not detected to prevent damage due to sensor failure. In addition, even if a failure occurs, it is not immediately detected, which worsens the process loss. Therefore, in order to prevent damage caused by such a sudden sensor failure, it is necessary to identify the failure of the sensor in an embedded system in real-time and to diagnose the failure and determine the type for a quick response. In this paper, a deep neural network-based fault diagnosis system is designed and implemented using Raspberry Pi to classify typical sensor fault types such as erratic fault, hard-over fault, spike fault, and stuck fault. In order to diagnose sensor failure, the network is constructed using Google's proposed Inverted residual block structure of MobilieNetV2. The proposed scheme reduces memory usage and improves the performance of the conventional CNN technique to classify sensor faults.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.262-269
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• 2020

Recently, many attempts have been made to reduce the time required for payment in various shopping environments. In addition, for the Fourth Industrial Revolution era, artificial intelligence is advancing, and Internet of Things (IoT) devices are becoming more compact and cheaper. So, by integrating these two technologies, access to building an unmanned environment to save people time has become easier. In this paper, we propose a smart shopping cart system based on low-cost IoT equipment and deep-learning object-detection technology. The proposed smart cart system consists of a camera for real-time product detection, an ultrasonic sensor that acts as a trigger, a weight sensor to determine whether a product is put into or taken out of the shopping cart, an application for smartphones that provides a user interface for a virtual shopping cart, and a deep learning server where learned product data are stored. Communication between each module is through Transmission Control Protocol/Internet Protocol, a Hypertext Transmission Protocol network, a You Only Look Once darknet library, and an object detection system used by the server to recognize products. The user can check a list of items put into the smart cart via the smartphone app, and can automatically pay for them. The smart cart system proposed in this paper can be applied to unmanned stores with high cost-effectiveness.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.75-80
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• 2018

The smart city is developing an energy system efficiently through a common management of the city resource for the growth and a low carbon social. However, the smart city doesn't counter a verification effectively about a anomaly pattern detection when existing security technology (authentication, integrity, confidentiality) is used by fixed security key and key deodorization according to generated big data. This paper is proposed the "security nonce generation based on security nonce generation" for anomaly pattern detection of the adversary and a safety of the key is high through the key generation of the KDC (Key Distribution Center; KDC) for improvement. The proposed scheme distributes the generated security nonce and authentication keys to each facilities system by the KDC. This proposed scheme can be enhanced to the security by doing the external pattern detection and changed new security key through distributed security nonce with keys. Therefore, this paper can do improving the security and a responsibility of the smart city platform management data through the anomaly pattern detection and the safety of the keys.