Recent advances in low power communication, power electronics, and unmanned aerial vehicles (UAV) technologies enable introducing UAVs to wireless sensor networks (WSN) applications, promising to extend the applicability of the Internet of Things concept to remote and hazardous environments. UAVs, as a data link, can remove the barrier of acquiring sensing information from otherwise disconnected devices. As a power link, meanwhile, continuous operation of sensors may be supported through wireless charging. However, design of low power communication protocols considering mobility remains an open issue. There are scant reported experiments of using UAVs to carry transmit coils for wireless charging, nor navigation solutions for UAVs to find sensor nodes requiring charging. This thesis proposes solutions to the challenges of communication and power linkages in this context. A cross-layer UAV integrated WSN protocol (UIWP) is designed and implemented for wireless communications between UAV and terrestrial wireless sensors. Experimental evaluation shows the proposed protocol to have good energy efficiency, low latency and high reliability. To boost the communication bit rate, dynamic switching between the IEEE 802.15.4 and Bluetooth Low Energy physical layers are implemented within UIWP, where the Bluetooth mode consumes about half the time and energy for transmitting the same amount of data. To solve the problem of navigating the UAV to the optimal charging point, an energy efficient sensor node was designed and built incorporating ultra-wide band technology to improve ranging. Its corresponding energy models were developed to determine charging frequency. Extended Kalman filter and navigation control algorithms are proposed for UAV positioning and navigation. The algorithms fuse sensing data, telemetry information and communication data to control the flight of the UAV, intended to achieve centimetre scale accuracy.