A Scalable Matching Mechanism for Online Heterogeneous Positioning Fusion System
Journal
IEEE Radio and Wireless Symposium, RWS
Journal Volume
2022-January
Pages
138-141
Date Issued
2022
Author(s)
Chen C.-Y
Abstract
Wi-Fi fingerprint positioning has the advantages of being infrastructure-less and easily accessible, but the weaknesses in terms of lower accuracy and limited Wi-Fi scanning speed are also hard to tackle. On the other hand, with the progress in computer vision and deep learning, vision-based positioning based on commonly available surveillance cameras becomes a promising solution for providing location-based services. But the major difficulty lies in checking the identity of detected people just by the captured images. This paper proposed a novel Matching Mechanism to address the identity matching problem, which associates the non-identifiable positioning sources like vision to the easily identifiable positioning sources like smart phone's Wi-Fi. Practicalities like scalability and online operation are considered in both the design and implementation of the mechanism. As a result, the experiment not only proved the effectiveness of matching the vision-based and Wi-Fi positioning results but also showed an improvement in positioning accuracy by over 60%. © 2022 IEEE.
Subjects
Computer Vision; Internet of Things; Location-based service; Object-detection model; Wi-Fi fingerprinting
SDGs
Other Subjects
Computer vision; Deep learning; Encoding (symbols); Internet of things; Network security; Object detection; Security systems; Smartphones; Telecommunication services; Wireless local area networks (WLAN); Fusion systems; Location-based services; Matching mechanisms; Matching problems; Object-detection model; Scanning speed; Smart phones; Surveillance cameras; Vision-based positioning; Wi-fi fingerprinting; Location based services
Type
conference paper