Mobile Crowd Sensing and Computing
By Bin Guo, Zhu Wang, Zhiwen Yu, Yu Wang, Neil Yuwen Yen, Runhe Huang, Xingshe Zhou. 2015
434 citations recorded by the source corpus.
Subfields: Computer Science Applications, Electrical and Electronic Engineering, Transportation
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
- Billy Pik Lik Lau
- U-Xuan Tan
- Yuren Zhou
- Meng Zhang
- Naveed Ul L. Hassan
- Marakkalage Sumudu Hasala
- Chau Yuen
- Andrea Passarella
In Transportation
- Robin I. M. Dunbar
- Chau Yuen
- Billy Pik Lik Lau
- Andrea Passarella
- Marco Conti
- U-Xuan Tan
- Danilo Bzdok
Citations in the corpus
- A survey of data fusion in smart city applications (2019, background): “• S3: Participatory Data Sources Participatory data sources include crowdsensing [90], [91] and crowdsourcing [92], [93] data contributed by the personal devices, e.g. mobile phones, wearable devices, tablets, etc. of the users in smart city.”
- The structure of online social networks mirrors those in the offline world (2015, background): “The people-centric sensing (also known as crowdsensing or participatory sensing ) paradigm combines wireless communications nd sensor networks with human’s daily life activities to sense the hysical world by exploiting the billions of connected users’ moile devices/phones, without deploying an addit”
- Federated Learning in Smart City Sensing: Challenges and Opportunities (2020, neutral): “With the growth of mobile Internet technology and applications, mobile smart devices have been widely used and greatly popularized [44].”