The Rise of People-Centric Sensing

By Andrew T. Campbell, Shane B. Eisenman, N. Lane, Emiliano Miluzzo, Ronald A. Peterson, Hong Lu, Xiao Zheng, Mirco Musolesi, K. Fodor, Gahng-Seop Ahn. IEEE Internet Computing, 2008

669 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Science Applications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/73fba6980dcf004a93471c8d53f93e5a73b47c30

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Citations in the corpus

The rise of low-cost sensing for managing air pollution in cities. (2015, background): “14 opportunistic sensing, which is using the data collected for one purpose for multiple other purposes as well (Campbell et al. 2008).”
Opportunistic IoT: Exploring the harmonious interaction between human and the internet of things (2013, background): “, supporting the so-called participatory sensing [10]; 2) it particularly explores the co-existing of opportunistic communities in the physical world and online communities in the virtual world, and study the interaction and collaboration between heterogeneous communities.”
A Survey on Internet of Things From Industrial Market Perspective (2015, background): “Facebook, Myspace, Twitter, and Foursquare) has been fused with the other context information retrieved through mobile devices to build novel context-aware applications such as activity predictions, recommendations, and personal assistance [17].”
Sensor Fusion for Public Space Utilization Monitoring in a Smart City (2017, methodology): “of WSN application in urban area are listed as follows: City Wide Deployment [1]–[3], Smart Metering [4], [5], Security Surveillance System [6], health-care [7], etc.”
Data Collection in Wireless Sensor Networks with Mobile Elements: A Survey (2011, background): “Mobile peers can also be used for opportunistic data collection in urban sensing scenarios [Campbell et al. 2006, 2008].”
PRISM: platform for remote sensing using smartphones (2010, background): “Some of this work has been in the context of the Metrosense project [10] on people-centric sensing.”
Human-Data Interaction: The Human Face of the Data-Driven Society (2014, background): “Such devices can create “people-centric” sensor trails (Campbell et al., 2008).”
Internet of Things and Big Data Analytics for Smart and Connected Communities (2016, background): “Further, peoplecentric sensing can be categorized into three classes: personal sensing, which focuses on personal monitoring and archiving; social sensing, which focuses on sharing information within social and special interest groups; and public sensing, which focuses on sharing data with everyone ”
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”
Incentives for Mobile Crowd Sensing: A Survey (2016, background): “have enabled and stimulated the development of mobile sensing technologies [1]–[5], among which mobile crowd sens-”
NoiseTube: Measuring and mapping noise pollution with mobile phones (2009, background): “Their individual stories of everyday life can be aggregated to document the urban environment, fed back into a collective experience in urban public spaces, enabling peoplecentric sensing [5], for personal, peer or public purposes.”
Security and Privacy Issues in Wireless Sensor Networks for Healthcare Applications (2010, background): “A new concept of ‘ people centric ’ and ‘ urban ’ wireless sensor networking has been proposed and gaining momentum day by day [1].”
Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application (2008, background): “, Nokia N95 and Apple iPhone) combined with the recent interest by the mobile phone vendors and cellular industry in open programming environments and platforms, typified by the recent release of the Android platform [2] and the Apple iPhone SDK [1], is accelerating the development of new people-cen”
Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis (2015, background): “Mobility and other contextual information are increasingly collected by means of mobile phone sensing applications [7], i.”
From opportunistic networks to opportunistic computing (2010, background): “An important contribution to characterizing the social context comes from multimodal sensing devices, which enable capturing rich sensing information that can be used to infer user activities [3].”
Looking ahead in pervasive computing: Challenges and opportunities in the era of cyber-physical convergence (2012, neutral): “edu/) investigates the concept of people-centric sensing [55].”
Opportunities in mobile crowd sensing (2014, background): “This sensing paradigm is popularly called mobile crowd sensing (MCS) [4, 5] or people/humancentric sensing [6].”