In this master thesis, I performed the energy profiling of the WebRTC frame- work on top of a resource-constrained platform. WebRTC is a standard so- lution for real-time video streaming, and it is an appealing solution in a wide range of application scenarios. This work focus on the use case of unmanned aerial vehicles distributing real-time video streams over a WebRTC session to a peer on the ground. The Raspberry Pi is a reference platform in the single- board computer category thus, it has been used as streaming device. A large testbed has been conducted to emulate the scenario under consideration. The testbed shows the empirical relationship between power consumption and QoE metrics such as PSNR and SSIM, highlighting the configurations that enable an energy-efficient WebRTC-based video-streaming.