Quality of Information in Mobile Crowdsensing
ACM Transactions on Sensor Networks, 2017 Smartphones have become the most pervasive devices in people’s lives and are clearly transforming the way we live and perceive technology. Today’s smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as an accelerometer, a gyroscope, a microphone, and a ...
Francesco Restuccia 0001 +4 more
openaire +2 more sources
A Review of Advanced Localization Techniques for Crowdsensing Wireless Sensor Networks
Sensors, 2019 The wide availability of sensing modules and computing capabilities in modern mobile devices (smartphones, smart watches, in-vehicle sensors, etc.) is driving the shift from mote-class wireless sensor networks (WSNs) to the new era of crowdsensing WSNs ...
Angelo Coluccia, Alessio Fascista
doaj +1 more source
Path Forming of Healthcare Practitioners in an Indoor Space Using Mobile Crowdsensing. [PDF]
Sensors (Basel), 2022 Panlaqui BJ, Fuad M, Deb D, Mickle C.
europepmc +1 more source
Frontiers in Aging Neuroscience, 2017 For understanding the heterogeneity of tinnitus, large samples are required. However, investigations on how samples recruited by different methods differ from each other are lacking.
Thomas Probst +12 more
doaj +1 more source
A Personalized Task Allocation Strategy in Mobile Crowdsensing for Minimizing Total Cost. [PDF]
Sensors (Basel), 2022 Gao H, Zhao H.
europepmc +1 more source
IEEE Access, 2019 Edge computing recently is increasingly popular due to the growth of data size and the need of sensing with the reduced center. Based on Edge computing architecture, we propose a novel crowdsensing framework called Edge-Mediated Spatial-Temporal ...
Sijia Yang +5 more
doaj +1 more source
PARS: Privacy-Aware Reward System for Mobile Crowdsensing Systems. [PDF]
Sensors (Basel), 2021 Zhang Z, Yum DH, Shin M.
europepmc +1 more source
Edge-enabled Mobile Crowdsensing to Support Effective Rewarding for Data Collection in Pandemic Events. [PDF]
J Grid Comput, 2021 Foschini L +3 more
europepmc +1 more source
Space-Air-Ground Integrated Mobile Crowdsensing for Partially Observable Data Collection by Multi-Scale Convolutional Graph Reinforcement Learning. [PDF]
Entropy (Basel), 2022 Ren Y, Ye Z, Song G, Jiang X.
europepmc +1 more source
A Generic Framework for Mobile Crowdsensing: A Comprehensive Survey
IEEE AccessMobile Crowdsensing (MCS) has emerged as a powerful paradigm for aggregating sensory data through the collaborative efforts of various mobile devices. Despite the innovative solutions inherent in this paradigm, it also introduces new challenges.
Abderrafi Abdeddine +2 more
doaj +1 more source