Uni-Fi: Integrated Multi-Task Wi-Fi Sensing
Mengning Li, Wenye Wang

TL;DR
Uni-Fi is an extensible framework that unifies multi-task Wi-Fi sensing, improving performance in localization, activity recognition, and presence detection through a scalable, integrated pipeline.
Contribution
It introduces a unified theoretical framework and a scalable sensing pipeline for multi-task Wi-Fi sensing integration, addressing key challenges in the field.
Findings
Median localization error of 0.54 meters
98.34% accuracy in activity classification
98.57% accuracy in presence detection
Abstract
Wi-Fi sensing technology enables non-intrusive, continuous monitoring of user locations and activities, which supports diverse smart home applications. Since different sensing tasks exhibit contextual relationships, their integration can enhance individual module performance. However, integrating sensing tasks across different studies faces challenges due to the absence of: 1) a unified architecture that captures the fundamental nature shared across diverse sensing tasks, and 2) an extensible pipeline that accommodates future sensing methodologies. This paper presents UNI-FI, an extensible framework for multi-task Wi-Fi sensing integration. This paper makes the following contributions: 1) we propose a unified theoretical framework that reveals fundamental differences between single-task and multi-task sensing; 2) we develop a scalable sensing pipeline that automatically generates a…
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Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Context-Aware Activity Recognition Systems · Mobile Crowdsensing and Crowdsourcing
