DroneVLC: Exploiting Drones and VLC to Gather Data from Batteryless Sensors

Abstract

We explore a new alternative for drones to gather information from sensors. Instead of using the traditional radiofrequency spectrum, whose broadcast nature makes it more difficult to poll specific objects, we utilize the light spectrum. In our system, the drone carries a light, and flies to an area that it is interested in polling. Only the sensor (tag) under the coverage of the light sends data back by backscattering the impinging light waves. Enabling this system poses two challenges. First, a reliable modulation method with light is required. The method must overcome noise dynamics introduced by the drone (mechanical oscillations), the object (backscattering effects) and the environment (interference from ambient light). Second, to facilitate the deployment of tags in pervasive applications, the design of the tag should be battery-less and have a small surface area. These requirements limit the amount of power available for reception, transmission and sensing, since the energy harvested by solar cells is proportional to their surface area. Regarding the first challenge, we show that the amplitude-based modulation methods used in state-of-the-art studies do not work in our scenario, and investigate instead a frequency-based approach. For the second challenge, we optimize the computation, reception and transmission of the tag to create a battery-less design that operates with frequency-modulated signals generated from light. We build a prototype for the drone and the tag, and test them under different lighting scenarios: dark, indoors, and outdoors with sunlight. The results show that, under standard indoor lighting, our system can attain a polling range of 1.1 m with a data rate of 120 bps, while the tag operates with small solar cells and consumes less than 1 mW.