As part of the thesis, a system was created that gives remote users at http://www.nerezisca-meteo.com/ an insight into current meteorological data as well as historical data display. The parameters to be measured are temperature, humidity, air pressure, solar radiation, wind speed and direction, carbon dioxide, carbon monoxide and air quality. The system collects data from sensors using two Arduino microcontrollers and sends them over the local TCP / IP network using the MQTT protocol to the Raspberry PI on which uses the Node-RED framework to store data in a SQLite database and display meteorological data locally on the system application interface. Using the NGINX web server and Dataplicity service, the purchased web domain was redirected to the system application interface.
The figure shows the complete distributed system. It is divided into three subsystems. The Croduino Nova2 subsystem with the associated sensors is shown in brown, and the Arduino Industrial 101 subsystem with the associated sensors is shown in green. In the local network, they communicate with Raspbery PI through MQTT broker. The Raspberry PI subsystem is highlighted in red, with locally installed tools and services for storing and displaying data locally, and services for port forwarding to the Internet. The part that takes place on the Internet, outside the local network, is marked in blue, in order to give the remote user access to the Node-RED application of this system via the web domain.
Wiring diagram subsystem Arduino Industrial 101 (Fritzing)
Flow diagram of Arduino industrial 101 subsystem
Wiring diagram of Croduino Nova2 subsystem
Flow diagram of Croduino Nova2 subsystem
The third subsystem consists of a Raspbery PI microcomputer with SQLite database,NGINX web server, eclipse MQTT broker and a Node-RED framework. NGINX web server is used to reverse the proxy redirect port that displays the Node-RED application user interface to port 80 that supports the Dataplicity service. The user interface of the Node-RED application is redirected to the Dataplicity web service via a Dataplicity agent installed locally on the raspberry PI.