Towards Battery-Free Machine Learning and Inference in Underwater Environments
Main Authors: | Zhao, Yuchen, Afzal, Sayed Saad, Akbar, Waleed, Rodriguez, Osvy, Mo, Fan, Boyle, David, Adib, Fadel, Haddadi, Hamed |
---|---|
Other Authors: | Program in Media Arts and Sciences (Massachusetts Institute of Technology) |
Format: | Article |
Language: | English |
Published: |
ACM|The 23rd International Workshop on Mobile Computing Systems and Applications
2022
|
Online Access: | https://hdl.handle.net/1721.1/146279 |
Similar Items
-
Underwater Backscatter Localization: Toward a Battery-Free Underwater GPS
by: Ghaffarivardavagh, Reza, et al.
Published: (2021) -
Battery-free wireless imaging of underwater environments
by: Afzal, Sayed Saad, et al.
Published: (2022) -
Demo: Battery-Free Wireless Underwater Camera
by: Rademacher, Jack, et al.
Published: (2023) -
Enabling Higher-Order Modulation for Underwater Backscatter Communication
by: Afzal, Sayed Saad, et al.
Published: (2022) -
Ultra-Wideband Underwater Backscatter via Piezoelectric Metamaterials
by: Ghaffarivardavagh, Reza, et al.
Published: (2021)