3.8 Proceedings Paper

A WiFi-based System for Recognizing Fine-grained Multiple-Subject Human Activities

出版社

IEEE
DOI: 10.1109/I2MTC48687.2022.9806622

关键词

Human Activity Recognition; Fine-grained Activity; WiFi-based Activity Recognition

向作者/读者索取更多资源

This paper proposes a new approach for recognizing fine-grained human activities using CSI and RSSI WiFi data, achieving a high accuracy rate of 97.5%.
Device-free human activity recognition has become a topic of much interest in recent years. While there is much existing work on course-grained human activity recognition, the recognition of fine-grained human activities is still a research challenge. In this paper, we propose a new approach using CSI and RSSI WiFi data to recognize fine-grained human activities. We selected 4 different fine-grained human activities from a human-to-human interaction dataset and defined some frequency features over CSI and RSSI data to use as input to our classification model. Using some classification methods and the K Nearest Neighbors (KNN) classifier, we achieved 97.5% of accuracy in fine-grained human activity recognition.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据