Tweeting with Sunlight
Encoding Data on Mobile Objects
Rens Bloom (AMS Institute)
Marco Zuñiga Zamalloa (AMS Institute, TU Delft - Embedded Systems)
Q. Wang (Katholieke Universiteit Leuven)
Domenico Giustiniano (IMDEA Networks Institute)
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Abstract
We analyze and optimize the performance of a new type of channel that exploits sunlight for wireless communication. Recent advances on visible light backscatter have shown that if mobile objects attach distinctive reflective patterns to their surfaces, simple photosensors deployed in our environments can decode the reflected light signals. Although the vision is promising, only initial feasibility studies have been performed so far. There is no analysis on how much information this channel can transmit or how reliable the links are. Achieving this vision is a complex endeavour because we have no control over (i) the sun or clouds, which determine the amount and direction of light intensity, and (ii) the mobile object, which determines the modulated reflection of sunlight. We investigate the impact of the surrounding light intensity and physical properties of the object (reflective materials, size and speed) to design a communication system that optimizes the encoding and decoding of information with sunlight. Our experimental evaluation, performed with a car moving on a regular street, shows that our analysis leads to significant improvements across many dimensions. Compared to the state of the art, we can encode seven times more information, and decode this information reliably from an object moving three times faster (53km/h) at a range that is four times longer (4m) and with three times lower light intensity (cloudy day).