실시간 객체 검출 기술 YOLOv5를 이용한 스마트 엘리베이터 시스템에 관한 연구
A Study on the Elevator System Using Real-time Object Detection Technology YOLOv5
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
본 논문에서는 YOLO(You only look once)v5를 기반으로 한 실시간 객체 검출 기술을 활용하여 스마트 엘리베이터 시스템을 연구하였다. 외부 엘리베이터 버튼이 눌러지면 YOLOv5 모델이 카메라 영상을 분석하여 대기자의유무를 판별하고, 대기자가 없다고 판별되면 해당 버튼을 자동으로 취소시킨다. 연구에서는 YOLOv5와 사물인터넷에서 활용되는 MQTT(Message Queuing Telemetry Transport)를 통한 객체 탐지 및 통신 기술의 효과적인 구현 방법을 소개한다. 그리고 이를 활용하여 대기자 유무를 실시간으로 판별하는 스마트 엘리베이터 시스템을 구현하였다. 제안한 시스템은 불필요한 소비 전력을 절감하면서 CCTV(closed-circuit television)의 역할을 할 수 있다. 따라서 제안한스마트 엘리베이터 시스템은 안전 및 치안 문제에도 기여할 수 있을 것으로 기대한다.
Abstract
In this paper, a smart elevator system was studied using real-time object detection technology based on YOLO(You only look once)v5. When an external elevator button is pressed, the YOLOv5 model analyzes the camera video to determine whether there are people waiting, and if it determines that there are no people waiting, the button is automatically canceled. The study introduces an effective method of implementing object detection and communication technology through YOLOv5 and MQTT (Message Queuing Telemetry Transport) used in the Internet of Things. And using this, we implemented a smart elevator system that determines in real time whether there are people waiting. The proposed system can play the role of CCTV (closed-circuit television) while reducing unnecessary power consumption. Therefore, the proposed smart elevator system is expected to contribute to safety and security issues.
참고문헌 (18)
- S. W. Jeon, "YOLO-based lane detection system", Journal of the Korea Institute of Information and Communication Engineering, 25(3), pp.464~470 (2021)
- "YOLO: Real-Time Object Detection"[URL]
- S. I. Kim, "A model to secure storage space for CCTV video files using YOLO v3", Journal of the Korea Society of Computer and Information, 28(1), pp.65~70 (2023)
- G. H. Jo, "Parallel U-Net Based Semantic Segmentation Method Using Generated Data from YOLO V5", The Journal of Korean Institute of Communications and Information Sciences, 48(3), pp.319~326 (2023)
- B. Peng, "Implementation of IoT-Based Hydroponic Cultivation System", Journal of Internet of Things and Convergence, 9(4), pp.56~69 (2023)
- J. H. Moon, "Implementation of Smart Umbrella Stand Based on IoT", Journal of Internet of Things and Convergence, 9(1), pp.57~64 (2023)
- "Raspberry Pi"[URL]
- INNOPOLIS Foundation, "Smart Elevator Market", ~ (2019)
- S. B. Park, "A Study on the Smart Elevator System for Home Using YOLO", The Korea Multimedia Society Spring conference 2023, 26(1), pp.89~91 (2023)
- S. H. Chun, "Smart Door Implementation Using Jetson Nano-Based OpenCV and Deep Learning", The Journal of Korean Institute of Communications and Information Sciences, 46(2), pp.380~387 (2021)
- D. J. Kim, "Smart Streetlight based on Accident Recognition using Raspberry Pi Camera OpenCV", The Journal of The Korea Institute of Electronic Communication Sciences, 17(6), pp.1229~1236 (2022)
- K. W. Lee, "Deep Learning-Based Worker Personal Protective Equipment and Face Identification System", Journal of Knowledge Information Technology and Systems, 17(3), pp.385~394 (2022)
- H. K. Bahn, "Efficient Scheduling of Sensor-based Elevator Systems in Smart Buildings", Journal of the Korea Academia-Industrial cooperation Society, 17(10), pp.367~372 (2016)
- "Glenn Jocher"[URL]
- "COCO - Common Objects in Context"[URL]
- "nenona Dataset"[URL]
- D. Lee, "Malicious Traffic Detection Method using LSTM and Sliding Window in MQTT based IoT Environment", The Journal of Korean Institute of Information Technology, 21(5), pp.111~120 (2023)
- "MQTT - The Standard for IoT Messaging"[URL]