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Lucan De Groot

dblp:345/2431 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Internet of things and sensor networks · 61% Physical-layer communications · 30% Vehicular, aerial and satellite networks · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks
backscatter communication
0.712023
DroneVLC: Exploiting Drones and VLC to Gather Data from Batteryless Sensors · PERCOM 2023
Internet of things and sensor networks › iot devices › battery-free devices
batteryless sensor
0.712023
DroneVLC: Exploiting Drones and VLC to Gather Data from Batteryless Sensors · PERCOM 2023
Physical-layer communications › optical wireless communication
visible light communication
0.712023
DroneVLC: Exploiting Drones and VLC to Gather Data from Batteryless Sensors · PERCOM 2023
Vehicular, aerial and satellite networks
UAV communication
0.212023
DroneVLC: Exploiting Drones and VLC to Gather Data from Batteryless Sensors · PERCOM 2023

Methods — techniques the papers use, named apart from their topics

frequency modulation · 0.7backscattering · 0.7
YearPublicationVenuePosition
2023 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 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.
Lucan De Groot, Talia Xu, Marco Zuniga
PERCOM1