Changes between Version 12 and Version 13 of other/summer/2019/fitness-assist

Timestamp:

Aug 6, 2019, 5:17:53 PM (5 years ago)

Author:

JustinEsposito

Comment:

—

other/summer/2019/fitness-assist

@@ -23 +23 @@
 We used a TP-LINK router at the 5GHz frequencies. To receive the CSI data from !WiFi, we used a Dell Laptop with an Ubuntu 14.02 kernal and an Intel !Wifi Wireless Link 5300 MIMO radio (IWL5300). We used the Linux 802.11n CSI Tool (created by Daniel Halperin, Wenjun Hu, Anmol Sheth, and David Wetherall), which is built off of the IWL5300. This tool allowed us to collect and read CSI data on the client computer.
 
-Using Python, we created a socket server on a Dell G3 laptop equipped with Windows 10. Additionally, we modified a fork of the tool (fork by Piotr Gawlowicz) to turn the binary streams of CSI data into complex numbers which we could then graph and perform computations with. For graphing, we used PyQt5, a GUI toolkit, !yQtGraph, a lightweight plotting module that has improved performance for real-time plotting of data. For our deep learning, we used !TensorFlow, a popular library used for machine learning.
+Using Python, we created a socket server on a Dell G3 laptop equipped with Windows 10. Additionally, we modified a fork of the tool (fork by Piotr Gawlowicz) to turn the binary streams of CSI data into complex numbers which we could then graph and perform computations with. For graphing, we used PyQt5, a GUI toolkit, !PyQtGraph, a lightweight plotting module that has improved performance for real-time plotting of data. For our deep learning, we used !TensorFlow, a popular library used for machine learning.
 
 == Exercises ==