poster

Which One is Correct, The Map or The GPS Trace

Authors:

Abdeltawab Hendawi,

Sree Sindhu Sabbineni,

Mohamed AliAuthors Info & Claims

SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Pages 472 - 475

https://doi.org/10.1145/3347146.3359099

Published: 05 November 2019 Publication History

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Abstract

GPS data is noisy by nature. A typical location-based service would start by filtering out the noise from the raw GPS points that are generated by moving objects. Once the locations of the objects are identified, the location-based service is provided. In this paper, we decide not to throw away the noise. Instead, we consider the noise as an asset. We analyze the various noise patterns under different conditions and region characteristics. More specifically, we focus on one example where a lot of GPS noise is experienced; which is urban canyons. We believe that learning the GPS noise patterns in a supervised environment enables us to discover knowledge about new areas or areas where we have little knowledge. This paper is based on the analysis of GPS traces that are collected from the shuttle service within the Microsoft campuses around Seattle, Washington.

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Oshanreh MMalarkey DMacKenzie D(2024)AI-Driven Feedback Systems Reduce Sidewalk Riding on Shared E-ScootersFindings10.32866/001c.125892Online publication date: 19-Nov-2024
https://doi.org/10.32866/001c.125892
Ahmadian SGollapudi SKollias KKumar VVelingker AVelusamy SChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Efficient Location Sampling Algorithms for Road NetworksCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3651497(899-902)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3651497
Du CSamonte M(2024)Research on Vehicle GPS Dynamic Sampling Based on Deep Reinforcement Learning2024 9th International Symposium on Computer and Information Processing Technology (ISCIPT)10.1109/ISCIPT61983.2024.10672728(492-498)Online publication date: 24-May-2024
https://doi.org/10.1109/ISCIPT61983.2024.10672728
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Index Terms

Which One is Correct, The Map or The GPS Trace
1. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
      1. Location based services

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Published In

SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2019

648 pages

ISBN:9781450369091

DOI:10.1145/3347146

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 November 2019

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SIGSPATIAL '19

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SIGSPATIAL

SIGSPATIAL '19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 5 - 8, 2019

IL, Chicago, USA

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SIGSPATIAL '19 Paper Acceptance Rate 34 of 161 submissions, 21%;

Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Oshanreh MMalarkey DMacKenzie D(2024)AI-Driven Feedback Systems Reduce Sidewalk Riding on Shared E-ScootersFindings10.32866/001c.125892Online publication date: 19-Nov-2024
https://doi.org/10.32866/001c.125892
Ahmadian SGollapudi SKollias KKumar VVelingker AVelusamy SChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Efficient Location Sampling Algorithms for Road NetworksCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3651497(899-902)Online publication date: 13-May-2024
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Du CSamonte M(2024)Research on Vehicle GPS Dynamic Sampling Based on Deep Reinforcement Learning2024 9th International Symposium on Computer and Information Processing Technology (ISCIPT)10.1109/ISCIPT61983.2024.10672728(492-498)Online publication date: 24-May-2024
https://doi.org/10.1109/ISCIPT61983.2024.10672728
Qu BZhao MFeng JWang X(2022)ASRL: An Adaptive GPS Sampling Method Using Deep Reinforcement Learning2022 23rd IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM55031.2022.00042(153-158)Online publication date: Jun-2022
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