Active crowd sensing

  1. Yu, Zhiyong
  2. Wang, Jiangtao
  3. Espada, Jordán Pascual 1
  1. 1 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

Revista:
Personal and Ubiquitous Computing

ISSN: 1617-4909,  1617-4917

Año de publicación: 2021

Volumen: 27

Número: 3

Páginas: 507-508

Tipo: Artículo

DOI: 10.1007/S00779-021-01564-X GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Personal and Ubiquitous Computing

Referencias bibliográficas

  • Tao D, Gao R, Sun H (2021) Sensing-gain constrained participant selection mechanism for Mobile Crowdsensing. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01470-8
  • Dai X, Shang F, Xing T, Chen F, Liu B (2021) LAR: a low power, high-precision Mobile phone-based AR system. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01421-3
  • Cheng S, Fan J, Hu Y (2021) Visual saliency model based on crowdsourcing eye tracking data and its application in visual design. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01463-7
  • He X, Liu M, Yang G. (2021) Spatiotemporal opportunistic transmission for Mobile crowd sensing networks. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01439-7
  • Ren Y, Wang T, Zhang S, Zhang J (2021) An intelligent big data collection technology based on micro Mobile data centers for Crowdsensing vehicular sensor network. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01440-0
  • Zhao D, Zhou Z, Wang S, Liu B, Gaaloul W (2021) Reinforcement learning-enabled efficient data gathering in underground wireless sensor networks. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01443-x
  • Shi Y, Zhang X, Hu Q, Cheng H (2021) Data recovery algorithm based on generative adversarial networks in crowd sensing internet of things. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01428-w
  • Zhao J, Chen C, Huang H, Xiang C (2021) Unifying Uber and taxi data via deep models for taxi-passenger demand prediction. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01426-y
  • Gao J, Zheng D, Yang S (2021) Perceiving spatiotemporal traffic anomalies from sparse representation-Modeled City dynamics. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01474-4
  • Zhou B, Chen L, Zhao S, Li S, Pan G (2021) Spatio-temporal analysis of urban crime leveraging multisource Crowdsensed data. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01456-6