UAV-Assisted Active Sparse Crowdsensing for Ground Signal Map Construction Based on 3-D Spatial-Temporal Correlation
C Liu, K Zhu, C Tao, B Chen… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Mobile crowdsensing (MCS) has been applied for signal map construction in smart city.
MCS leverages the mobility of users and the sensors embedded in mobile phones to collect …
MCS leverages the mobility of users and the sensors embedded in mobile phones to collect …
UAV-assisted ground signal map construction based on 3-D spatial correlation
Mobile crowdsensing (MCS) has been applied for signal map construction in smart city.
However, it is still costly for MCS to cover large-scale regions. Accordingly some data …
However, it is still costly for MCS to cover large-scale regions. Accordingly some data …
Spatiotemporal fracture data inference in sparse mobile crowdsensing: A graph-and attention-based approach
Mobile Crowdsensing (MCS) is a sensing paradigm that enables large-scale smart city
applications, such as environmental sensing and traffic monitoring. However, traditional …
applications, such as environmental sensing and traffic monitoring. However, traditional …
Energy-Efficient 3-D Data Collection forMulti-UAV Assisted Mobile Crowdsensing
Mobile CrowdSensing (MCS) is an emerging paradigm that employs massive mobile
devices (MDs) to complete sensing tasks cooperatively. To provide ubiquitous MCS …
devices (MDs) to complete sensing tasks cooperatively. To provide ubiquitous MCS …
Active Sensing for Transformer Model in Sparse Mobile CrowdSensing
With the popularization of mobile devices and the development of 5G networks, Mobile
Crowd-Sensing (MCS) has emerged as a new paradigm for data collection. As its variant …
Crowd-Sensing (MCS) has emerged as a new paradigm for data collection. As its variant …
Fine-grained urban prediction via sparse mobile crowdsensing
Mobile CrowdSensing (MCS) has recently emerged as a practical paradigm for large-scale
and fine-grained urban sensing systems. To reduce sensing cost, Sparse MCS only senses …
and fine-grained urban sensing systems. To reduce sensing cost, Sparse MCS only senses …
Sparse mobile crowdsensing: challenges and opportunities
Sensing cost and data quality are two primary concerns in mobile crowd sensing. In this
article, we propose a new crowd sensing paradigm, sparse mobile crowd sensing, which …
article, we propose a new crowd sensing paradigm, sparse mobile crowd sensing, which …
Outlier-concerned data completion exploiting intra-and inter-data correlations in sparse crowdsensing
Mobile CrowdSensing (MCS) is a popular data collection paradigm which usually faces the
problem of sparse sensed data because of the limited sensing cost. In order to address the …
problem of sparse sensed data because of the limited sensing cost. In order to address the …
Spatiotemporal fracture data inference in sparse urban crowdsensing
While Mobile CrowdSensing (MCS) has become a popular paradigm that recruits mobile
users to carry out various sensing tasks collaboratively, the performance of MCS is …
users to carry out various sensing tasks collaboratively, the performance of MCS is …
Spatiotemporal urban inference and prediction in sparse mobile crowdsensing: A graph neural network approach
Mobile CrowdSensing (MCS) has recently become a promising data acquisition paradigm,
which recruits a large number of users to collect data from the target sensing areas …
which recruits a large number of users to collect data from the target sensing areas …