• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1254-1262
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• 2021

Recently, the agricultural environment in Korea is rapidly changing due to the aging and decline of the agricultural population, and in order to solve these problems, it is urgently required to improve the agricultural productivity and reduce the labor force. To solve this problem, a smart farm fused with ICT technology is being proposed as an alternative. In Korea, smart farms are currently mainly used in greenhouses. In this paper, this smart farm technology is to be applied to the cultivation of sprouted ginseng. To this end, we use seedlings (about 1.0g) to grow a solid medium and bed for cultivating sprouted ginseng, a fresh ginseng that is produced in a short period of time (2~3 months) with a clean environment management technology that does not use chemical pesticides and hydroponics in a greenhouse developed. In addition, an IoT-based growth environment management system was developed to monitor the growth process of sprouted ginseng in such an environment and to control driving devices.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.377-389
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• 2021

This paper presents a framework design of a digital twin system for a vertical smart farm. In this paper, a framework of digital twin systems establishes three factors: 1) Client 2) IoT gateway, and 3) Server. Especially, IoT gateway was developed using the Eclipse Ditto, which has been commonly used as the standard open hardware platform for digital twin. In particular, each factor is communicating with the client, IoT gateway, and server by defining the message sequence such as initialization and data transmission. In this paper, we describe the digital twin technology trend and major platform. The proposed design has been tested in a testbed of the lab-scale vertical smart-farm. The sensor data is received from 1 Jan to 31 Dec 2020. In this paper, a prototype digital twin system that collects environment and control data through a raspberry pi in a plant factory and visualizes it in a virtual environment was developed.

• Journal of Practical Engineering Education
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• v.10 no.1
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• pp.9-15
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• 2018

A digital signage is constructed using a speech recognition based API, and VRSM (Voice Recognition Smart Mirror) that obtains information such as weather, map, exercise information, schedule, and image by user's voice command so as to be different from other commercialized products is proposed. This course provides an effective method of engineering education through the process of being evaluated as the result of independent graduation certification system, and also it had been the opportunity to design and produce works for 3 semesters by 2 students one group in the majors. Through the comprehensive capstone design, it has experienced engineering approach and creative thinking opportunity. We have won the best academic prize by participating in the academic conferences of the institute about the interim result, and obtained the results of the prize contest in other academic conferences. The improvement in practical skills obtained through this process proved to be beneficial for self-confidence and job-seeking opportunities through actual employment.

• Convergence Security Journal
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• v.22 no.1
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• pp.29-38
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• 2022

The importance of prevention of epidemics is increasing due to the serious spread of infectious diseases. For prevention of epidemics, we need to focus on the non-contact industry. Therefore, in this paper, a face recognition door lock that controls access through non-contact is designed and developed. First very simple features are combined to find objects and face recognition is performed using Haar-based cascade algorithm. Then the texture of the image is binarized to find features using LBPH. An non-contact door lock system which composed of Raspberry PI 3B+ board, an ultrasonic sensor, a camera module, a motor, etc. are suggested. To verify actual performance and ascertain the impact of light sources, various experiment were conducted. As experimental results, the maximum value of the recognition rate was about 85.7%.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1661-1669
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• 2017

In 2017, Korea has reached 1.3 million elderly people living alone. The government is promoting the basic care service for the elderly by using care workers to check the security of the elderly living alone. However, due to lack of service personnel and service usage rate of elderly care workers, it is difficult to manage. To improve these environmental constraints, this study attempted to construct a monitoring system for elderly people living alone by using sensors such as temperature, humidity, motion detection, and gas leak detection. The sensor periodically collects the current status data of the elderly and sends them to the server, creates a real time graph based on the data, and monitors it through the web. In the monitoring process, when the sensor is out of the range of the specified value, it sends a warning text message to the guardian to inform the current situation, and is designed and implemented so as to support the safety life of the elderly living alone.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.115-121
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• 2020

With the spread of IoT technology, various IoT applications using facial recognition are emerging. This paper describes the design and implementation of a remote control system using deep learning-based face recognition and hand gesture recognition. In general, an application system using face recognition consists of a part that takes an image in real time from a camera, a part that recognizes a face from the image, and a part that utilizes the recognized result. Raspberry PI, a single board computer that can be mounted anywhere, has been used to shoot images in real time, and face recognition software has been developed using tensorflow's FaceNet model for server computers and hand gesture recognition software using OpenCV. We classified users into three groups: Known users, Danger users, and Unknown users, and designed and implemented an application that opens automatic door locks only for Known users who have passed both face recognition and hand gestures.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.175-182
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• 2022

In our daily life, we come across different types of information, for example in the format of multimedia and text. We all need different types of information for our common routines as watching/reading the news, listening to the radio, and watching different types of videos. However, sometimes we could run into problems when a certain type of information is required. For example, someone is listening to the radio and wants to listen to jazz, and unfortunately, all the radio channels play pop music mixed with advertisements. The listener gets stuck with pop music and gives up searching for jazz. So, the above example can be solved with an automatic audio classification system. Deep Learning (DL) models could make human life easy by using audio classifications, but it is expensive and difficult to deploy such models at edge devices like nano BLE sense raspberry pi, because these models require huge computational power like graphics processing unit (G.P.U), to solve the problem, we proposed DL model. In our proposed work, we had gone for a low complexity model for Audio Event Detection (AED), we extracted Mel-spectrograms of dimension 128×431×1 from audio signals and applied normalization. A total of 3 data augmentation methods were applied as follows: frequency masking, time masking, and mixup. In addition, we designed Convolutional Neural Network (CNN) with spatial dropout, batch normalization, and separable 2D inspired by VGGnet [1]. In addition, we reduced the model size by using model quantization of float16 to the trained model. Experiments were conducted on the updated dataset provided by the Detection and Classification of Acoustic Events and Scenes (DCASE) 2020 challenge. We confirm that our model achieved a val_loss of 0.33 and an accuracy of 90.34% within the 132.50KB model size.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1581-1587
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• 2021

As embedded system are used widely and variously, multi-edge system, which multiple edges gather and perform complex operations together, is actively operating. In a multi-edge system, it often occurs that an abnormal operation at one edge is transferred to another edge or the entire system goes down. It is necessary to determine and control edge anomalies in order to prevent system down, but this can be a heavy burden on the resource-limited edge. As a solution to this, we use power consumption data to check the state of the edge device and transmit it based on a QRcode to check and control errors at the server. The architecture proposed in this paper is implemented using 'chip-whisperer' to measure the power consumption of the edge and 'Raspberry Pi 3' to implement the server. As a result, the proposed architecture server showed successful data transmission and error determination without additional load appearing at the edge.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.57-64
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• 2023

In this paper, we propose a smart umbrella stand based on the Internet of Things (IoT) that helps people to pack their umbrellas more easily. The proposed smart umbrella stand offers three functions. First, it receives weather information, and a hidden umbrella handle will automatically become visible when it rains, making it easier to grab. Second, the smart umbrella stand is equipped with a heated air system, allowing it to effectively dry umbrellas that have become wet due to rain. This makes it more convenient for users to dry and store their rain-soaked umbrellas. Third, the smart umbrella stand enables users to monitor its current status, track weather conditions, and monitor the water level in the rain gutter through a dedicated application. The proposed smart umbrella stand aims to bring convenience to daily life by making it more convenient to carry an umbrella on rainy days or days with a high probability of rain.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.470-470
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• 2023

하천 및 저수지의 수량자료 수집을 위해 부자식 또는 레이더식 수위계 등의 계측기를 이용하여 수위의 변화를 측정한다. 그러나, 수량 모니터링을 위해 설치되는 계측기와 유지관리를 위한 인력소모 비용의 이유로 일부 지역에서만 제한적으로 수행되고 있어 정확한 수문 해석에 한계가 있다. 이에 본 연구에서는 저가의 센싱장비와 라즈베리파이를 활용한 ICT 기술을 수량 모니터링분야에 적용하여 수위 모니터링 기술을 개발하고자 한다. 라즈베리파이(Raspberry Pi 3 B Model)는 오픈소스 기반의 초소형 컴퓨터로 여러 센서를 연결하여 다양한 수문 인자(토양수분, 온도, 수위 등)들을 측정할 수 있으며, 통신 모듈이 기본 내장되어 있어 통신망 구축을 통해 측정데이터를 데이터베이스에 저장할 수 있다. 수위센서(eTape)와 초음파센서를 연결하여 실제 하천 유량 모니터링에 활용되고 있는 부자식 수위계 장비와 비교 분석을 통해 활용 가능성을 검증하고자 하였다. 검증방법은 인공강우실험을 위해 설치된 플륨관에 수위센서(eTape)와 초음파센서를 부착하여 기존 운영중인 부자식 수위계와 비교하였다. 부자식 수위계의 측정결과와 두 센서의 상관관계를 분석한 결과 결정계수(R²)가 0.94 이상으로 나타났다. 분석결과와 같이 기존 고가의 수위 관측장비들을 대체하여 저가의 센서 기반 모니터링 장비들의 실용화가 가능할 것이라 판단된다. 향후 연구에서는 다양한 센서(수위, 초음파, 카메라 등)를 이용하여 농업용수 물수지 분석에 활용할 계획이다. 농업용수는 수자원 총량 중 차지하는 비율이 높음에도 불구하고 정량적 데이터가 부족한 실정이며, 지역별 공급 특성이 다양하여 이를 계량화하기 위해서는 다수의 계측기가 필요하다. 따라서, 본 연구에서 개발중인 센서를 활용하여 물순환 과정의 정량적인 계측을 통해 농업용수의 효율적인 관리 및 농업용수의 하천기여도 평가 자료로 활용될 수 있을 것으로 판단된다.