1 . Database Instruction :
We have our own MySQL database used to stored all the data we collected, you can scan it by opening the terminal and typing the following command to install MySQL :
On Ubuntu : type in "sudo apt-get install mysql"
On Mac : type in "sudo brew install mysql"
Then log in our database. Due to privacy, please refer to our Readme.txt wrapped in submitted code section, we put the account and password in it.
After logging in, you will have all permissions to see our project data stored in it. If you have any problem logging into it, please also refer to the Readme.txt, there's a more detailed tutorial.
On Ubuntu : type in "sudo apt-get install mysql"
On Mac : type in "sudo brew install mysql"
Then log in our database. Due to privacy, please refer to our Readme.txt wrapped in submitted code section, we put the account and password in it.
After logging in, you will have all permissions to see our project data stored in it. If you have any problem logging into it, please also refer to the Readme.txt, there's a more detailed tutorial.
2 . View The Data We Collected
We used two tables to store air quality related data. The name of first table is Airquality, which was used to store temperature and air quality index collected from project parts, and the second table is named Dustinfo, we stored the dust data in it, and picked concentration attribute of it to represent dust data for analysis.
After logging into our database , there are some useful commands to scan it, for example, you can type in :
"SELECT * FROM Dustinfo;" after the "mysql>" showed on the command line, this will display all the dust data we collected from project parts.
You can also type in "SELECT * FROM Airquality;" to scan the temperature and air quality as well.
(Note : the category "iotdata" is collected in bathroom, we mistyped a wrong name, except for this, other places are correctly typed in)
All the data we used for analysis in the following sub slides were based on these data, totally over sixty thousand sample points.
After logging into our database , there are some useful commands to scan it, for example, you can type in :
"SELECT * FROM Dustinfo;" after the "mysql>" showed on the command line, this will display all the dust data we collected from project parts.
You can also type in "SELECT * FROM Airquality;" to scan the temperature and air quality as well.
(Note : the category "iotdata" is collected in bathroom, we mistyped a wrong name, except for this, other places are correctly typed in)
All the data we used for analysis in the following sub slides were based on these data, totally over sixty thousand sample points.