Parking Lot Occupancy Detection using Deep Learning and Fisheye Camera for AIoT System

• 영문명: Parking Lot Occupancy Detection using Deep Learning and Fisheye Camera for AIoT System
• 발행기관: 한국스마트미디어학회
• 저자명: To Xuan Dung Seongwon Cho
• 간행물 정보: 『스마트미디어저널』Vol13, No.1, 24~35쪽, 전체 12쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2024.01.31

영문 초록

The combination of Artificial Intelligence and the Internet of Things (AIoT) has gained significant popularity. Deep neural networks (DNNs) have demonstrated remarkable success in various applications. However, deploying complex AI models on embedded boards can pose challenges due to computational limitations and model complexity. This paper presents an AIoT-based system for smart parking lots using edge devices. Our approach involves developing a detection model and a decision tree for occupancy status classification. Specifically, we utilize YOLOv5 for car license plate (LP) detection by verifying the position of the license plate within the parking space.

목차

Ⅰ. INTRODUCTION

Ⅱ. RELATED WORK

Ⅲ. METHODOLOGY

Ⅳ. EXPERIMENT AND RESULTS

Ⅴ. CONCLUSION

REFERENCES

키워드

AIoT YOLOv5 Decision Tree Fisheye Camera