RF
This is the dataset we collected for the article "Scalable Undersized Dataset RF Classification: Using Convolutional Multistage Training". 17 objects were collected in the laboratory and scanned using a 'cw radar' setup featuring 2x UWB antennas (1 transmit antenna, 1 receive antenna), inside anechoic chamber. There was no clutter added in the experiment.
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An energy harvester for a smart contact lens that monitors the glucose level of a user is developed and demonstrated. The energy harvester captures a smartphone’s 2G cellular emission, and rectifies it into DC power to operate on-lens microelectronics for glucose detection and wireless data transmission. The energy harvester can reach a maximum Ra- dio Frequency (RF) to Direct Current (DC) power conversion efficiency of 47%. An electrically realistic human eye model is designed and fabricated using 3D printing technologies to assist in various measurements of the proposed energy harvester.
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