############################################################################################
The S&M-HSTPM2d5 dataset: High Spatial-Temporal Resolution PM 2.5 Measures in Multiple
Cities Sensed by Static & Mobile Devices, Version 1.0.0									
############################################################################################

This Read_Me.txt file provides a brief description of the S&M-HSTPM2d5 dataset and
instructions to access it. By deploying static and mobile devices in three Chinese cities
(Foshan, Cangzhou, Tianjin), real PM2.5 measures are collected in each city with high
spatial and temporal resolution. S&M-HSTPM2d5 dataset contains the measures of PM2.5
concentration, timestamps, and GPS records of static and mobile devices. 

The dataset is available at:

https://10.5281/zenodo.4028130

The data descriptor paper with details of data collection and cleaning process is under
submission. For proper citation of the manuscript, please refer to the latest version of
this dataset which includes the details.

This dataset and its descriptor paper were created by:

Xinlei Chen, Xinyu Liu, Kent Xin Kin Eng, Jingxiao Liu, Hae Young Noh, Lin Zhang, and Pei Zhang

For questions or suggestions please e-mail Xinlei Chen <xinlei.chen@sv.cmu.edu>

============================================================================================
Description
============================================================================================

This S&M-HSTPM2d5 dataset contains the high spatial and temporal resolution of the PM2.5 
measures with the corresponding timestamp and GPS location of mobile and static devices in 
the three Chinese cities: Foshan, Cangzhou, and Tianjin. Different numbers of static and 
mobile devices were set up in each city. The sampling rate was set up as one minute in 
Cangzhou, and three seconds in Foshan and Tianjin. For the specific detail of the setup, 
please refer to the Device_Setup_Description.txt file in this repository and the data
descriptor paper.

After the data collection process, the data cleaning process was performed to remove and
adjust the abnormal and drifting data. The script of the data cleaning algorithm is provided
 in this repository. The data cleaning algorithm only adjusts or removes individual data
points. The removal of the entire device's data was done after the data cleaning algorithm
with empirical judgment and graphic visualization. For specific detail of the data cleaning
process, please refer to the script (Data_cleaning_algorithm.ipynb) in this repository and
the data descriptor paper.

The dataset in this repository is the processed version. The raw dataset and removed 
devices are not included in this repository.

The data is stored as a CSV file. Each CSV file which is named by the device ID represents
the data that was collected by the corresponding device. Each CSV file has three types of
data: timestamp as the China Standard Time (GMT+8), geographic location as latitude and
longitude, and PM2.5 concentration with the unit of microgram per cubic meter. The CSV 
files are stored in either Static or Mobile folder which represents the devices' type. 
The Static and Mobile folder are stored in the corresponding city's folder.

To access the dataset, any programming language that can access CSV files is appropriate.
Users can also open the CSV file directly. The get_dataset.ipynb file in this repository
also provides an option of accessing the dataset. To successfully execute ipynb file,
Jupyter Notebook with Python 3.0 is required. The following python library is also required:

get_dataset.ipynb:
	1. os library
	2. pandas library

Data_cleaning_algorithm.ipynb:
	1. os library
	2. pandas library
	3. datetime library
	4. math library

The instruction of installing the libraries above can be found online. After installing the
Jupyter Notebook with Python 3.0 and the required libraries, users can try to open the ipynb
file with Jupyter Notebook and follow the instruction inside the file. 

============================================================================================
File list
============================================================================================
Please first unzip the /S&M-HSTPM2d5/Cangzhou.zip
                       /S&M-HSTPM2d5/Foshan.zip
                       /S&M-HSTPM2d5/Tianjin.zip

/S&M-HSTPM2d5/
	Read_Me.txt                                              This file

	Device_Setup_Description.txt				 Description of the setup
								 of individual device in
								 each city
	
	Data_cleaning_algorithm.ipnyb				 Script that is used in
								 data cleaning process

	get_dataset.ipnyb					 Script for accessing the
								 dataset

	Cangzhou/
		Static/
			id_1.csv                                 Individal static device's 
			id_2.csv                                 data in Cangzhou. Each csv
			...					 file represent one device
		Mobile/
			id_1.csv                                 Individal mobile device's 
			id_2.csv                                 data in Cangzhou. Each csv
			...					 file represent one device

	Foshan/
		Static/
			id_1.csv                                 Individal static device's 
			id_2.csv                                 data in Foshan. Each csv
			...					 file represent one device
		Mobile/
			id_1.csv                                 Individal mobile device's 
			id_2.csv                                 data in Foshan. Each csv
			...					 file represent one device


	Tianjin/
		Static/
			id_1.csv                                 Individal static device's 
			id_2.csv                                 data in Tianjin. Each csv
			...					 file represent one device
		Mobile/
			id_1.csv                                 Individal mobile device's 
			id_2.csv                                 data in Tianjin. Each csv
			...					 file represent one device