Using LoPy IoT devices to measure a city's conditions

The general data flow of the system is as follows:

Advantages of this system:

• System can be expanded with more devices very easily.
• The map view is very quick, as there is no overhead of the server.
• The data is stored centrally and thus can be accessed from any computer.
• SQL operations can be done on the data before it is served.

Located here.
This is the micro-python code that is uploaded to the LoPy device.
It reads a range of measurements from the PySense module and sends the data if there has been a significant change (10%).

Located here.
This is the Java application used to view data from the devices.

The main views of the application are:

• Map view using Google Maps, (implemented in Java using JxMaps).
• Graph view showing the history of data received (uses JFreeChart).

Located here.
This is the Java code that stores all received data onto a SQL server.

The database is structured as below:

A number of external libraries were used to create this project.

These include:

• JFreeChart - to create graphs on MapApp.
• JxMaps - to display a map on MapApp.
• OpenWeatherMap Java API by xSAVIKx - to display data from OpenWeatherMap on MapApp.
• TheThingsNetwork Java API - to receive data from TTN on MapApp and DataServer.
• PySense library - to read data from PySense.

These are some websites which were extremely useful when creating this project.

• Official PyCom documentation.
• The Things Network usage guide.
• Latitude and Longitude of a location.