An Analysis of Device-Free and Device-Based WiFi-Localization Systems

TL;DR

This paper introduces an automated fingerprint construction tool for WiFi localization and analyzes how various environmental and technical factors impact the accuracy of device-based and device-free WiFi localization systems.

Contribution

It presents a novel automated fingerprinting tool and provides a comprehensive analysis of factors affecting WiFi localization accuracy in different scenarios.

Findings

AP mounting location significantly affects accuracy

AP technology upgrades influence localization performance

Crowd effects impact calibration and operation

Abstract

WiFi-based localization became one of the main indoor localization techniques due to the ubiquity of WiFi connectivity. However, indoor environments exhibit complex wireless propagation characteristics. Typically, these characteristics are captured by constructing a fingerprint map for the different locations in the area of interest. This fingerprint requires significant overhead in manual construction, and thus has been one of the major drawbacks of WiFi-based localization. In this paper, we present an automated tool for fingerprint constructions and leverage it to study novel scenarios for device-based and device-free WiFi-based localization that are difficult to evaluate in a real environment. In a particular, we examine the effect of changing the access points (AP) mounting location, AP technology upgrade, crowd effect on calibration and operation, among others; on the accuracy of the localization system. We present the analysis for the two classes of WiFi-based localization: device-based and device-free. Our analysis highlights factors affecting the localization system accuracy, how to tune it for better localization, and provides insights for both researchers and practitioners.