  Wireless power transfer (WPT) is a promising technology to prolong the
lifetime of sensor and communication devices, i.e., workers, in completing
crowdsourcing tasks by providing continuous and cost-effective energy supplies.
In this paper, we propose a wireless powered spatial crowdsourcing (SC)
framework which consists of two mutual dependent phases: task allocation phase
and data crowdsourcing phase. In the task allocation phase, we propose a
Stackelberg game based mechanism for the SC platform to efficiently allocate
spatial tasks and wireless charging power to each worker. In the data
crowdsourcing phase, the workers may have an incentive to misreport its real
working location to improve its own utility, which manipulates the SC platform.
To address this issue, we present a strategyproof deployment mechanism for the
SC platform to deploy its mobile base station. We apply the Moulin's
generalized median mechanism and analyze the worst-case performance in
maximizing the SC platform's utility. Finally, numerical experiments reveal the
effectiveness of the proposed framework in allocating tasks and charging power
to workers while avoiding the dishonest worker's manipulation.
