使用 Yolo V8 算法的智能婴儿监控系统

Er.M. Meena, Dr.G Ramesh
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引用次数: 2

摘要

使用 YOLO V8 算法的智能婴儿监控系统旨在利用先进的计算机视觉技术加强婴儿监控。该项目利用 YOLO(You Only Look Once)第 8 版这一最先进的物体检测算法,通过 Python 和 Tensor Flow 或 PyTorch 等框架实现,以检测和跟踪实时视频馈送中的物体。该系统具有面部识别功能,可识别已知的护理人员,并具有异常活动或紧急情况警报机制。用户界面通过网络或移动应用程序为护理人员提供实时警报、可视化和历史数据分析。通过利用 YOLO V8 在物体检测方面的高效率以及 Python 在数据处理和集成方面的能力,该系统旨在增强安全性、提高护理效率,并让父母和护理人员放心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SMART BABY MONITORING SYSTEM USING YOLO V8 ALGORITHM
The Smart Baby Monitoring System using the YOLO V8 algorithm is designed to enhance infant monitoring by leveraging advanced computer vision techniques. This project utilizes YOLO (You Only Look Once) version 8, a state-of-the-art object detection algorithm, implemented with Python and frameworks like Tensor Flow or PyTorch, to detect and track objects in real-time video feeds. The system incorporates features for facial recognition to identify known caregivers and alert mechanisms for unusual activities or emergencies. The user interface provides real-time alerts, visualizations, and historical data analysis for caregivers via a web or mobile application. By leveraging YOLO V8's efficiency in object detection and Python's capabilities for data processing and integration, this system aims to enhance safety, improve care giving efficiency, and provide peace of mind to parents and caregivers.
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