https://github.com/netreconlab/icnc20
A light-weight simulator used to illustrate the use of Delay Tolerant Networks as a supplement for Cloud Connectivity for Rural Remote Patient Monitoring.
https://github.com/netreconlab/icnc20
mhealth
Last synced: 6 months ago
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A light-weight simulator used to illustrate the use of Delay Tolerant Networks as a supplement for Cloud Connectivity for Rural Remote Patient Monitoring.
- Host: GitHub
- URL: https://github.com/netreconlab/icnc20
- Owner: netreconlab
- Created: 2019-08-22T01:15:17.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-12-28T22:22:20.000Z (almost 5 years ago)
- Last Synced: 2025-02-06T04:41:28.226Z (8 months ago)
- Topics: mhealth
- Language: Jupyter Notebook
- Homepage:
- Size: 90.8 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ICNC20
This repository contains a *light-weight simulator used to illustrate the use of Delay Tolerant Networks as a supplement for Cloud Connectivity for Rural Remote Patient Monitoring.
## Code Navigation
* `classification.csv`: A csv file containing the daily acivities and their classifications.
* `activity_tracker.ipynb`: A jupyter notebook containing the analysis of the Mobility Sample Data.
* `simulation.ipynb`: A jupyter notebook for running a simulation and analyzing results of a simulation
## Publications
For more information about the simulator, please refer to our paper. If you use this simulator or code in your own work, we are happy to receive a citation.
Esther Max-Onakpoya, Oluwashina Madamori, Faren Grant, Robin Vander-pool, Ming-Yuan Chih, David K. Ahern, Eliah Aronoff-Spencer, and Corey E.Baker. 2019. Augmenting Cloud Connectivity with Opportunistic Networksfor Rural Remote Patient Monitoring.
[//]: #[[PDF](https://arxiv.org/pdf/1905.05342.pdf)]
## Comments
Based on the IPUMS ATUS terms and conditions, redistribution of ATUS data is not permitted https://www.atusdata.org/atus/terms.shtml. However, you may obtain an extract from their website: https://www.atusdata.org/atus-action/variables/group
To replicate our work, you would need to obtain the 2017 sample and use the following variables:
| Type | Variable | Label|
| --- | --- | --- |
| H | RECTYPE | Record Type|
| H | CASEID | ATUS Case ID|
| H | METRO | Metropolitan/central city status|
| P | FULLPART | Full time/part time employment status|
| A | ACTLINE | Activity line number|
| A | ACTIVITY | Activity|
| A | START | Activity start time|
| A | STOP | Activity stop time|
We converted the data from dat to the csv format ('b.csv' file), which had the following headings: RECTYPE, CASEID, METRO, FULLPART, ACTLINE, ACTIVITY, START, STOP. A viable way to do the conversion is by using the syntax file to extract and read the data via SAS, SPSS, or STATA to convert the data to csv.