.png){kind=icon}
.png){kind=icon}
Return
Context-aware computing for mobile crowd sensing: A survey
.png){kind=icon}
PRE
AI
DOI：10.1016/j.future.2019.04.052.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Today, the distribution of people with smart mobile devices has provided the opportunity for mobile crowd sensing. Several mobile crowd sensing systems have led to the collection of valuable information with a low infrastructural investment. These types of information have been used in context-aware systems to provide high-level services. In this paper, a comprehensive reference framework is proposed to investigate context-aware mobile crowd sensing systems from three viewpoints of concepts, context-awareness, and functionalities. Each of these aspects has one or more parameters, which investigate and classify the existing works. To this end, the paper characterizes domain and cooperation type, context-awareness, incentive mechanisms, data sharing, local analysis and global aggregation of mobile crowd sensing systems. The aim is to thoroughly review the existing works, foster the dissemination of state-of-the-art research, and present future research directions. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Mobile crowd sensing
Context-awareness
Functionalities
Survey
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
F
IF:
6.1
Papers:
6.8K
Citations:
2.3W