Title
DroneVLC: Exploiting Drones and VLC to Gather Data from Batteryless Sensors
Author
de Groot, Lucan (Student TU Delft)
Xu, M. (TU Delft Networked Systems)
Zuniga, Marco (TU Delft Networked Systems) 
Date
2023
Abstract
We explore a new alternative for drones to gather information from sensors. Instead of using the traditional radio-frequency 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.
Subject
Visible Light Communication
Backscatter
Bat-teryless
Drones
UAV
Dynamic Channel
To reference this document use:
http://resolver.tudelft.nl/uuid:e9fba20c-c71c-48c8-9867-9248eda9c06c
DOI
https://doi.org/10.1109/PERCOM56429.2023.10099247
Publisher
IEEE, Danvers
Embargo date
2023-10-18
ISBN
978-1-6654-5379-0
Source
Proceedings of the 2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Event
2023 IEEE International Conference on Pervasive Computing and Communications (PerCom), 2023-03-13 → 2023-03-17, Atlanta, United States
Series
2023 IEEE International Conference on Pervasive Computing and Communications, PerCom 2023
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
conference paper
Rights
© 2023 Lucan de Groot, M. Xu, Marco Zuniga