VeLoc: Finding your car in indoor parking structures
Sensors (Switzerland), ISSN: 1424-8220, Vol: 18, Issue: 5
2018
- 3Citations
- 8Captures
- 1Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations3
- Citation Indexes3
- CrossRef3
- Captures8
- Readers8
- Mentions1
- Blog Mentions1
- Blog1
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Sensors, Vol. 18, Pages 1403: VeLoc: Finding Your Car in Indoor Parking Structures
Sensors, Vol. 18, Pages 1403: VeLoc: Finding Your Car in Indoor Parking Structures Sensors doi: 10.3390/s18051403 Authors: Ruipeng Gao Fangpu He Teng Li While WiFi-based
Article Description
While WiFi-based indoor localization is attractive, there are many indoor places without WiFi coverage with a strong demand for localization capability. This paper describes a system and associated algorithms to address the indoor vehicle localization problem without the installation of additional infrastructure. In this paper, we propose VeLoc, which utilizes the sensor data of smartphones in the vehicle together with the floor map of the parking structure to track the vehicle in real time. VeLoc simultaneously harnesses constraints imposed by the map and environment sensing. All these cues are codified into a novel augmented particle filtering framework to estimate the position of the vehicle. Experimental results show that VeLoc performs well when even the initial position and the initial heading direction of the vehicle are completely unknown.
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