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Extending Coverage of Stationary Sensing Systems with Mobile Sensing Systems for Human Mobility Modeling

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Desheng ZhangAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 4, Issue 3

Article No.: 100, Pages 1 - 21

https://doi.org/10.1145/3411827

Published: 04 September 2020 Publication History

Abstract

Human mobility modeling has many applications in location-based services, mobile networking, city management, and epidemiology. Previous sensing approaches for human mobility are mainly categorized into two types: stationary sensing systems (e.g., surveillance cameras and toll booths) and mobile sensing systems (e.g., smartphone apps and vehicle tracking devices). However, stationary sensing systems only provide mobility information of human in limited coverage (e.g., camera-equipped roads) and mobile sensing systems only capture a limited number of people (e.g., people using a particular smartphone app). In this work, we design a novel system Mohen to model human mobility with a heterogeneous sensing system. The key novelty of Mohen is to fundamentally extend the sensing coverage of a large-scale stationary sensing system with a small-scale sensing system. Based on the evaluation on data from real-world urban sensing systems, our system outperforms them by 35% and achieves a competitive result to an Oracle method.

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Cited By

Lee YSong WSong JNoh Y(2024)Extending EV Battery Lifetime: Digital Phenotyping Approach for Departure Time PredictionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997258:4(1-30)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3699725
Atrey AZakaria CBalan RShenoy P(2024)W4-Groups: Modeling the Who, What, When and Where of Group Behavior via Mobility SensingProceedings of the ACM on Human-Computer Interaction10.1145/36374278:CSCW1(1-29)Online publication date: 26-Apr-2024
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Index Terms

Extending Coverage of Stationary Sensing Systems with Mobile Sensing Systems for Human Mobility Modeling
1. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
      1. Location based services

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 4, Issue 3

September 2020

1061 pages

EISSN:2474-9567

DOI:10.1145/3422862

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Copyright © 2020 ACM.

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Published: 04 September 2020

Published in IMWUT Volume 4, Issue 3

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Cited By

Lee YSong WSong JNoh Y(2024)Extending EV Battery Lifetime: Digital Phenotyping Approach for Departure Time PredictionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997258:4(1-30)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3699725
Atrey AZakaria CBalan RShenoy P(2024)W4-Groups: Modeling the Who, What, When and Where of Group Behavior via Mobility SensingProceedings of the ACM on Human-Computer Interaction10.1145/36374278:CSCW1(1-29)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637427
Cao ZZhao DSong HYuan HWang QMa HTong JTan C(2024) F 3 VeTrac: Enabling Fine-grained, Fully-road-covered, and Fully-individual penetrative Vehicle Trajectory Recovery IEEE Transactions on Mobile Computing10.1109/TMC.2023.3301871(1-16)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3301871
Yan HWang HZhang DYang YFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)Identifying Regional Driving Risks via Transductive Cross-City Transfer Learning Under Negative TransferProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3614924(2877-2886)Online publication date: 21-Oct-2023
https://dl.acm.org/doi/10.1145/3583780.3614924
Yan HYang Y(2023)Large-scale trajectory prediction via relationship-aware adaptive hierarchical graph learningCCF Transactions on Pervasive Computing and Interaction10.1007/s42486-023-00133-w5:4(351-366)Online publication date: 15-Jun-2023
https://doi.org/10.1007/s42486-023-00133-w
Zhong SLyu WZhang DYang Y(2022)BikeCAP: Deep Spatial-temporal Capsule Network for Multi-step Bike Demand Prediction2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS54860.2022.00085(831-841)Online publication date: Jul-2022
https://doi.org/10.1109/ICDCS54860.2022.00085
Lyu WWang GYang YZhang D(2021)MoverProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34949975:4(1-21)Online publication date: 30-Dec-2021
https://dl.acm.org/doi/10.1145/3494997
Fang ZYang YYang GXian YZhang FZhang D(2021)CellSenseProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34780875:3(1-22)Online publication date: 14-Sep-2021
https://dl.acm.org/doi/10.1145/3478087

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