@inproceedings{landikaPosterAbstractObstructionfree2023,
  title = {Poster Abstract: {{Obstruction-free Physiological Motion Sensing}} in {{NextG Networks}} with {{Intelligent Reflective Surfaces}}},
  booktitle = {Proceedings of the 8th {{ACM}}/{{IEEE}} Conference on Internet of Things Design and Implementation},
  author = {Landika, Denny Vishnu Puri and Dacuycuy, Saige and Zheng, Yao},
  date = {2023},
  series = {{{IoTDI}} '23},
  pages = {466--468},
  publisher = {Association for Computing Machinery},
  location = {New York, NY, USA},
  doi = {10.1145/3576842.3589171},
  url = {https://gustybear-websites.s3.us-west-2.amazonaws.com/publication-landika-poster-abstract-obstructionfree-2023/Landika+et+al_2023_Poster+abstract.pdf},
  abstract = {This poster abstract shows the possibilities of incorporating an Intelligent Reflective Surface (IRS) that operates at the 3.5 GHz band in order to enhance signal coverage and perform obstruction-free physiological motion sensing. At an operating frequency of 3.5 GHz, the IRS redirects an incoming signal at normal incidence to 34°. A testbed is developed that allows us to test the quality of periodic motion (i.e. simulate breathing). The transmit horn is pointed at a metallic target that is oscillating at 0.2 Hz, where the target scatters the transmitted signal. The scattered signal will reach the IRS, which then redirects the signal to the receive horn. The setup was tested for three possible cases, with an IRS, a copper plate, and an absorber as the target. The merits of implementing an IRS in physiological sensing are discussed and evaluated.},
  isbn = {9798400700378},
  keywords = {Intelligent Reflective Surface,NextG networks,Physiological Sensing}
}