• Journal of IKEEE
• /
• v.23 no.3
• /
• pp.777-784
• /
• 2019

A pre-fire awareness and automatic notification system are required because it is possible to minimize the damage if the fire situation is precisely detected after a fire occurs in a place where people are unusual or in a mountainous area. In this study, we developed a RaspberryPi-based fire recognition system using Faster-recurrent convolutional neural network (F-RCNN) and single shot multibox detector (SSD) and demonstrated a fire alarm system that works with power line communication. Image recognition was performed with a pie camera of RaspberryPi, and the detected fire image was transmitted to a monitoring PC through an inductive power line communication network. The frame rate per second (fps) for each learning model was 0.05 fps for Faster-RCNN and 1.4 fps for SSD. SSD was 28 times faster than F-RCNN.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.07a
• /
• pp.95-97
• /
• 2023

본 논문에서는 임베디드 기반의 다양한 센서를 활용한 드론의 비행기록장치 시스템 개발에 대한 새로운 아이디어를 제시한다. 이 시스템은 오픈소스 기반의 개발 보드인 라즈베리파이를 중심으로, 온도, 습도, 조도, 미세먼지 센서, 이산화탄소, 일산화탄소, 산소, 이산화질소, 아황산가스, 메탄가스, GPS, 고도 측정, IR 카메라, 카메라 모듈 센서 등 다양한 센서를 탑재하여 구성한다. 기존 드론은 주로 방역 및 방제 활동에 활용되었으나, 그 활동의 효과를 정밀하게 측정하고 분석하는 데에는 한계가 있었다. 그러나 이 논문에서 제안하는 임베디드 기반의 센서 구성은 이러한 한계를 극복할 수 있을 것으로 기대된다.

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

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.1
• /
• pp.93-100
• /
• 2020

In this paper, we implemented a smart mirror that helps users to measure the results before the procedure by reflecting various hairstyles on the head. When the camera is used to capture a face in real time and recognize the face, the stored hair image is uploaded to provide a virtual image. In addition, the high production cost, which is a problem of the existing smart mirrors, was reduced by using Raspberry Pi, Open CV, and half mirror film, and various functions were implemented through touch control. It is also designed to provide information such as weather, calendar and time.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.6
• /
• pp.565-570
• /
• 2015

In this paper, we implemented the smart door lock system that control remotely devices using the concept of internet of things. Internet of things is intelligent system that can help devices to communicate with people and devices. And recently internet of things is getting attention because of advance of hardware technology and big data. The smart doorlock system based on internet of things used raspberry pi, sensor and doorlock. Using the smart phone, doorlock can be controlled from the raspberry pi server. And the user can identify some people that is in front of doorlock. also user can check around of doorlock in realtime using the raspberry pi camera.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.1
• /
• pp.1-8
• /
• 2020

If a dangerous situation arises in a place where out of reach from the human, UAVs can be used to determine the size and location of the situation to reduce the further damage. With this in mind, this paper sets the minimum value of the roll, pitch, and yaw using beta flight to detect the UAV's smooth hovering, integration, and derivative (PID) values to ensure that the UAV stays horizontal, minimizing errors for safe hovering, and the camera uses Open CV to install the Raspberry Pi program and then HSV (color, saturation, Brightness) using the color palette, the filter is black and white except for the red color, which is the closest to the fire we want, so that the UAV detects the image in the air in real time. Finally, it was confirmed that hovering was possible at a height of 0.5 to 5m, and red color recognition was possible at a distance of 5cm and at a distance of 5m.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.649-649
• /
• 2015

최근 기후변화 및 이상기후로 인해 하천환경 또한 급격하게 변화되고 있다. 변화되는 지구환경에 대응하기 위해 하천환경 대책과 하천생태계 보전/복원, 생물 보호, 친수기능 강화를 요구하고 있는 실정이다. 더욱이 소하천 건천화 및 하천환경관리에 대한 중요성은 대두되고 있으나 비용 및 인력투입 문제로 수위나 유량 등의 기초자료인 수위-유량 계측기술 및 대응연구가 미미한 실정이다. 체계적인 하천관리를 위해서는 신뢰성 있는 대상 하천의 수리량 자료 확보가 기본으로 요구된다. 이러한 중소하천의 관리의 신뢰도를 높이기 위해서는 실시간 수위유량 자료 확보가 필수적이다. 현재 하천 정비 계획 단계에서 수문모델링을 통해 중소하천의 유량을 산정하고 있지만 산발적으로 측정한 자료로는 검/보정에 한계가 있으며, 신뢰도를 확보하기 어려운 실정이다. 이수, 환경, 생태 등의 관점에서는 평상시 유량에 대한 실시간 정보가 매우 중요하다. 이에 체계적인 하천관리를 위해서는 중소하천에 대한 실시간 수리량 자료를 경제적으로 확보 할 수 있는 장치 개발 및 현장적용이 시급하다. 본 연구에서는 하천 횡단구조물이 가지고 있는 유량 측정의 편이성을 최대한 이용하여 급성장하고 있는 영상분석기술과 IT을 하천공학분야에 접목하여 중소하천의 수위와 유량을 실시간으로 원격 측정하는 WIA (Wireless Image Acquisition) 시스템을 개발하였다. WIA 시스템은 라즈베리파이 기반으로 적외선카메라를 이용하여 일정한 시간간격으로 횡단구조물의 상류, 중류, 구조물 주위의 흐름 영상을 확보하여 중앙처리장치로 전송하는 시스템으로 구성된다. WIA 시스템에서 전송된 영상은 본 연구에서 개발한 영상판독 S/W 및 H-Q 산정 S/W를 통해 하천의 수위를 판독하고 실시간으로 하천단면 수위유량 산정 자료 구축하는 자료로 활용된다. 현재 WIA 시스템의 성능 및 개선과 영상판독 S/W 및 H-Q 산정 S/W서버와의 연계운영 성능 평가를 통해 장치를 검증하는 단계에 있으며, 추후 서버구축을 통해 홍수 예 경보와 하천수질관리를 위한 기초자료로 활용될 것으로 기대된다. 또한 본 연구에서 개발하는 유량측정 시스템을 적용하면 기존 장비의 약 15% 예산으로 실시간 수리량 자료를 확보할 수 있을 것으로 예상된다.

• Journal of the Institute of Convergence Signal Processing
• /
• v.19 no.4
• /
• pp.174-179
• /
• 2018

Currently, various security technologies such as fingerprint recognition and face recognition are being developed. However, although many technologies have been developed, the field of incorporating technologies is quite limited. In particular, it is easy to adapt modern security technologies into existing digital systems, but it is difficult to introduce new digital technologies in systems using analog systems. However, if the system can be widely used, it is worth replacing the analog system with the digital system. Therefore, the selected topic is the electronic attendance system. In this paper, a camera is installed to a door to perform a Haar-like feature training for face detecting and real-time face recognition with a Eigenface in principal component analysis(PCA) based face recognition using raspberry pi. The collected data was transmitted to the smartphone using wireless communication, and the application for the viewer who can receive and manage the information on the smartphone was completed.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.4
• /
• pp.99-105
• /
• 2023

In this paper, an intelligent CCTV was designed and experimentally developed by using an IOT device, Raspberry Pi, and artificial intelligence technology. Object Detection technology was used to detect the number of people on the CCTV screen, and Action Detection technology provided by OpenPose was used to detect emergency situations. The proposed system has a structure of CCTV, server and client. CCTV uses Raspberry Pi and USB camera, server uses Linux, and client uses iPhone. Communication between each subsystem was implemented using the MQTT protocol. The system developed as a prototype could transmit images at 2.7 frames per second and detect emergencies from images at 0.2 frames per second.

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