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AuthorLi, Mengyao
AuthorZhu, Rongbo
AuthorDing, Qianao
AuthorWang, Jun
AuthorWan, Shaohua
AuthorMa, Maode
Available date2023-12-03T11:07:39Z
Publication Date2023
Publication NameCluster Computing
ResourceScopus
ISSN13867857
URIhttp://dx.doi.org/10.1007/s10586-022-03682-4
URIhttp://hdl.handle.net/10576/50046
AbstractEdge computing enables portable devices to provide smart applications, and the indoor positioning technique offers accurate location-based indoor navigation and personalized smart services. To achieve the high positioning accuracy, an indoor positioning algorithm based on particle filter requires a large number of sample particles to approximate the probability density function, which leads to the additional computational cost and high fusion delay. Focusing on real-time and accurate positioning, an edge computing-enabled green multi-source fusion indoor positioning algorithm called APFP is proposed based on adaptive particle filter in this paper. APFP considers both pedestrian dead reckoning (PDR) signals in mobile terminals and the received signal strength indication (RSSI) of Bluetooth, and effectively merges the error-free accumulation of trilateral positioning and the accurate short-range positioning of PDR, which enables mobile terminals adaptively perform particle filter to reduce the computing time and power consumption while ensuring positioning accuracy simultaneously. Detailed experimental results show that, compared with the traditional particle filter algorithm and the map-constrained algorithm, the proposed APFP reduces fusion computing cost by 59.89% and 54.37%, respectively.
SponsorThis work was supported in part by the National Natural Science Foundation of China (No. 61772562), the Knowledge Innovation Program of Wuhan-Basic Research (No. 2662022YJ012), the Talent Foundation of Huazhong Agricultural University (No. 11042110018), and the Fundamental Research Funds for the Central Universities, South-Central MinZu University (No. CZZ21003).
Languageen
PublisherSpringer
SubjectAdaptive particle filter
Edge computing
Indoor positioning
Multisource fusion
Pedestrian dead reckoning (PDR)
TitleEdge computing-enabled green multisource fusion indoor positioning algorithm based on adaptive particle filter
TypeArticle
Pagination667-684
Issue Number1
Volume Number26
dc.accessType Abstract Only


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