Incentives for Mobile Crowd Sensing: A Survey

By Xinglin Zhang, Zheng Yang, Wei Sun, Yunhao Liu, Shaohua Tang, Kai Xing, Xufei Mao. IEEE Communications Surveys and Tutorials, 2016

505 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Federated Learning in Smart City Sensing: Challenges and Opportunities (2020, unknown): “Federated Learning can beneﬁt smart cities sensing in multiple aspects [32].”
A Survey of Wearable Devices and Challenges (2017, background): “[20] briefly surveyed the use of wearables as sensing units and similarly Harle [21] surveyed the use of wearables in indoor positioning applications.”
Privacy-Preserved Data Sharing Towards Multiple Parties in Industrial IoTs (2020, background): “This is the case where the service provider is just a basic platform for data fusion in IIoTs [39], and will not participate in the functionality of the production system.”
Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey (2016, background): “, [110]–[112], but they did not focus on”
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities (2019, background): “It is possible to classify the existing works on incentives into three categories [12]: entertainment, service, and money.”