Crowdsensing big data: sensing, data selection, and understanding
Shuying Zhai, Ru Li, Yuange Yang · Journal of Physics Conference Series · 2021
Abstract Mobile Crowdsensing (MCS) has become an emerging paradigm for large-scale sensing. It empowers ordinary citizens to contribute data sensed or generated from their mobile devices (e.g., smartphones, wearable devices), aggregates and fuses the data in the cloud for crowd intelligence extraction and human-centric service delivery. The data contributed by the crowd in MCS systems presents the features such as multi-modal, rich-content, spatio-temporal, and human-centric. The key challenges and techniques about crowdsensing big data were discussed. The recent progress of our group in this promising research area was described.