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@sensetogether

SenseTogether

Mobile Crowdsensing
  • Inria Paris

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  1. ContextSense ContextSense Public

    User-centric Context Inference for Mobile Crowdsensing

    Java 1

  2. BeTogether BeTogether Public

    Let Opportunistic Crowdsensors Work Together for Resource-efficient, Quality-aware Observations

    Java 1

  3. CalibrateNoiseTogether CalibrateNoiseTogether Public

    Multi-hop Multi-party Sensor Calibration: Enhancing the Accuracy of Mobile Crowdsensing at Scale

    Java

  4. IAM IAM Public

    IAM: Interpolation and Aggregation on the Move – A Collaborative Crowdsensing Approach for Spatio-temporal Phenomena

    Python

Repositories

Showing 4 of 4 repositories
  • CalibrateNoiseTogether Public

    Multi-hop Multi-party Sensor Calibration: Enhancing the Accuracy of Mobile Crowdsensing at Scale

    sensetogether/CalibrateNoiseTogether’s past year of commit activity
    Java 0 Apache-2.0 0 0 0 Updated Jul 24, 2020
  • ContextSense Public

    User-centric Context Inference for Mobile Crowdsensing

    sensetogether/ContextSense’s past year of commit activity
    Java 1 GPL-3.0 0 0 0 Updated Jul 24, 2020
  • BeTogether Public

    Let Opportunistic Crowdsensors Work Together for Resource-efficient, Quality-aware Observations

    sensetogether/BeTogether’s past year of commit activity
    Java 0 GPL-3.0 1 0 0 Updated Jul 24, 2020
  • IAM Public

    IAM: Interpolation and Aggregation on the Move – A Collaborative Crowdsensing Approach for Spatio-temporal Phenomena

    sensetogether/IAM’s past year of commit activity
    Python 0 GPL-3.0 0 0 0 Updated Jul 24, 2020

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