Changes between Version 3 and Version 4 of other/summer/2019/fitness-assist


Ignore:
Timestamp:
Jun 20, 2019, 5:14:39 PM (5 years ago)
Author:
JustinEsposito
Comment:

Added Tools section

Legend:

Unmodified
Added
Removed
Modified

  • other/summer/2019/fitness-assist

    v3 v4  
    11= ​Real-time Fitness Assistance via !WiFi =
    22
    3 **Project Description**
     3== Project Description ==
    44
    55Workers cannot dedicate appropriate time during the day to travel to dedicated exercise places. Instead, they perform their exercise in an office/home environment. Unfortunately, it is difficult to analyze their form while doing their exercises without incurring the significant cost of a personal trainer or the discomfort of smart sensors on their person. Our solution is a device-free personalized fitness assistant that analyzes the channel state information of existing !WiFi infrastructure.
    … …  
    77When completed, our system will differentiate individuals when they are performing an exercise and assess the workout in real time. To detect individuals, we plan on using a deep neural network (DNN) with two layers: one to differentiate between exercises, and one deeper layer to differentiate individuals. To assess the workout, we will analyze the workout quality and provide a workout review for individuals to improve their exercises.
    88
     9== Tools ==
     10
     11We used a TP-LINK router with 2.4GHz and 5GHz frequencies. We used a Dell Laptop with Ubuntu 14.02 and an Intel !WiFi Wireless Link 5300 MIMO radio, also known as the IWL5300. We used the Linux 802.11n CSI tool, created by Daniel Halperin, Wenjun Hu, Anmol Sheth, and David Wetherall, to extract the CSI from the channel measurements. For the machine learning, we used a two-layer deep neural network, implemented in Python and Tensorflow.
     12