User Guide¶
This guide explains how to use this package and obtain results published in our paper. Results can be re-generated automatically by executing the following commands:
$ rr-data 'datapath/'
$ rr-paper 'datapath/csh101/csh101.ann.features.csv' 'output/'
For your reference, the paper tables are repeated below, so you can check the reproducibility of our solution.
Working hypothesis¶
It is possible to perform human activity recognition using data from continuous ambient sensors
Dataset¶
The dataset that was used for this project is the UCI ML Repository’s Human Activity Recognition from Continuous Ambient Sensor Data Data Set [dua2019] [cook2012]. It represents ambient data collected in 30 homes with volunteer residents. Data are collected continuously while residents perform their normal routines. It contains 36 features measured plus one output for the classification label of the activity, for a total of 13956534 entries.
Machine learning¶
Random forest classifiers from scikit-learn were used to obtains the results presented in this project.