In this thesis, we show that it is possible to design a battery-free light sensing system that can sense and communicate hand gestures while operating fully on harvested power from indoor light. We present two main innovations that push our system to tens of microwatts of power to enable battery-free operation. First, we introduce a novel visible light sensing system that can track variations in light intensity by using a solar cell as a sensor. Solar cells are unlike photodiodes optimized for energy yield in the visible light region and hence do not require any power hungry active components such as an operational amplifier. Furthermore, solar cells can operate under more diverse light conditions as they are not susceptible to saturation under bright light. Second, we devise two ultra-low power communication mechanisms based on radio frequency backscatter to transmit sensor readings at various resolutions without the need of any energy-expensive computational blocks. We design two battery-free and self-powered hardware prototypes that are based on these two innovations. Our first design utilizes an on-board comparator based circuit to perform a 1-bit digitization of changes in light readings, consuming only sub-microwatt of power for digitization. For our second prototype, we design an analog backscatter mechanism that can map raw sensor readings directly to backscatter transmissions. We demonstrate the feasibility of our designs when sensing significant changes in light intensity caused by shadows from hand gestures, and reconstruct these at a receiving device. Our results demonstrate the ability to sense and communicate various hand gestures at a peak power of 20 microwatts when performing 1-bit digitization, and a mean power of 60 microwatts when performing analog backscatter. Both designs represent orders of magnitude improvement in terms of power consumption over state-of-the-art visible light sensing systems. / Battery-free Visible Light Sensing / MobiCom: G: Battery-free Visible Light Sensing
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-381370 |
| Date | January 2019 |
| Creators | Soleiman, Andreas |
| Publisher | Uppsala universitet, Avdelningen för datorteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UPTEC F, 1401-5757 ; 19002 |
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