XI INTERNATIONAL CONFERENCE
“INFORMATION TECHNOLOGY AND IMPLEMENTATION” (IT&I-2024)
Information System for Air Quality Assessment and Data Processing: Design and Implementation
Volodymyr Hnatushenko, Tetiana Bulana, Igor Gomilkо, Bohdan Molodets, Daniil Boldyriev
State of the art
Air quality monitoring systems are crucial for assessing and managing air pollution, especially in urbanized areas. Various innovative approaches have emerged that use technologies such as the Internet of Things (IoT) and machine learning (ML) to improve data collection, processing and analysis.
Mobile-based air pollution detection system scheme
DOI: https://doi.org/10.1155/2024/4895068
Schematic overview of the air monitoring system
DOI: https://doi.org/10.3390/electronics12081842
Objective
Create an information system which can:
The main results
The system is divided into the following parts: ground-based monitoring stations, a server that stores data from the station, and a web application that displays the data to the user.
Use case diagram
Sequence diagram for AQI info calculation
The main results
The data layer collects data from various sources
The parsers layer processes the collected data using Celery workers – workflows that receive data from various sources and transfer it to RabbitMQ for further processing.
The server layer is responsible for processing and storing data.
The client layer provides a user interface for accessing processed data via a website or mobile application.
Scheme of system
The main results
The following components are most commonly monitored in determining ambient air quality: nitrogen dioxide (NO2), ozone (O3), particulate matter up to 2.5 microns in size (PM2.5), particulate matter up to 10 microns in size (PM10), sulfur dioxide (SO2) and carbon monoxide (CO)
Monitoring station with ZE12 series electrochemical sensors.
Time dependence of SO2 concentration in the atmosphere for 4 ZE-12-SO2 type sensors placed in the same conditions.
The main results
MQ-series semiconductor sensors – are not interesting as they only register small emissions concentrations.
MICS series semiconductor sensors – can only detect very high concentrations of emission substances and require additional calibration.
Electrochemical sensors of the ZE03 series can be used for a rough estimation of harmful pollutants.
The most interesting sensors for the atmospheric air quality monitoring system are the electrochemical sensors of the ZE12 series, which were used to create the monitoring system
Results of the analysis of the tested sensors
The main results
There is a list of pollutants with measurement limits used for AQI calculation below:
Parameter characteristics of the parameters to be measured
Experiment results
The result of the development is a system for monitoring changes in air quality over time, reflecting the received and processed data from ground sensors, meteorological data, and satellite data in the form
Air quality map in developed information system
Experiment results
Electrochemical sensors ZE-12 were used as measuring elements in the system.
After receiving the data was processed, stored on SD card and transferred via WIFI or GSM (Global System for Mobile Communications) to the cloud storage. The device is controlled via Bluetooth. The system is powered from a 12V DC source. The entire system is housed in an enclosure that provides IP53 protection.
Station with sensors ZE-12 as outdoor device
Conclusions
The main design stages are covered, starting with the system requirements, hardware and sensors selection, and software development for data collection, transmission, and analysis. The implemented system ensures high accuracy and reliability of data, which allows for a prompt response to changes in air quality.
The advanced functionality of the sensors includes the ability to detect a variety of pollutants, such as fine dust (PM2.5 and PM10), ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and other harmful substances.
The system also can send alerts to users when high pollution levels are detected, which helps respond to potential health hazards in a timely manner. The architecture's flexibility allows for easy integration of additional sensors and modules to expand functionality and improve measurement accuracy.
Thank you for attention!