sarmadalij / activityrecognitionandresearch

About the Project

The project is based on the recognition of human activites through sensors in smartphones. For this purpose, we have analyzed and studied a dataset and research papers that we have included in this repository. The reference of the dataset and the research papers is duly mentioned in the acknowledgment section of this read me file.

In this project we have studied that how activity is predicted/recognized by using the acclerometer and GPS sensor in smartphones. To implement the recognition of the human activity the data is collected through controlled, laboratory conditions. And then we have analyzed and visualize this data in jupyter notebook. The data in this repo corresponds with the data used in the one of the research paper in our repo, titled as "Activity Recognition using Cell Phone Accelerometers" was conducted by the Department of Computer and Information Science of Fordham University, NY/USA.

Statistics of Dataset

Raw Time Series Data

Number of examples: 1,098,207

Number of attributes: 6

Missing attribute values: None

Class Distribution

Walking: 424,400 (38.6%)

Jogging: 342,177 (31.2%)

Upstairs: 122,869 (11.2%)

Downstairs: 100,427 (9.1%)

Sitting: 59,939 (5.5%)

Standing: 48,395 (4.4%)

Acknowledgment

Readme file for WISDM's activity prediction dataset v1.1 Updated: Dec. 2, 2012

This data has been released by the Wireless Sensor Data Mining (WISDM) Lab. http://www.cis.fordham.edu/wisdm/

The data in this file corrispond with the data used in the following paper:

Jennifer R. Kwapisz, Gary M. Weiss and Samuel A. Moore (2010). Activity Recognition using Cell Phone Accelerometers, Proceedings of the Fourth International Workshop on Knowledge Discovery from Sensor Data (at KDD-10), Washington DC. http://www.cis.fordham.edu/wisdm/public_files/sensorKDD-2010.pdf

When using this dataset, we request that you cite this paper.

You may also want to cite our other relevant articles, which can be found here: http://www.cis.fordham.edu/wisdm/publications.php

Jeffrey W. Lockhart, Tony Pulickal, and Gary M. Weiss (2012). "Applications of Mobile Activity Recognition," Proceedings of the ACM UbiComp International Workshop on Situation, Activity, and Goal Awareness, Pittsburgh, PA.

Gary M. Weiss and Jeffrey W. Lockhart (2012). "The Impact of Personalization on Smartphone-Based Activity Recognition," Proceedings of the AAAI-12 Workshop on Activity Context Representation: Techniques and Languages, Toronto, CA.

Jennifer R. Kwapisz, Gary M. Weiss and Samuel A. Moore (2010). "Activity Recognition using Cell Phone Accelerometers," Proceedings of the Fourth International Workshop on Knowledge Discovery from Sensor Data (at KDD-10), Washington DC.

When sharing or redistributing this dataset, we request that this readme.txt file is always included.

Files: readme.txt WISDM_ar_v1.1_raw_about.txt WISDM_ar_v1.1_trans_about.txt WISDM_ar_v1.1_raw.txt WISDM_ar_v1.1_transformed.arff

Changelog (v1.1):

• about files updated with summary information
• file naming convention updated to include version numbers
• readme.txt updated to include relevant papers
• WISDM_ar_v1.1_trans_about.txt updated with citation to paper describing the attributes.

Changelog (v1.0):

• user names masked with ID numbers 1-36
• dataset initialized

Thanks!