Air monitoring system based on IoT

Abstract

A number of researches associated the level of the COVID-19 corona virus lethality with the air pollution level. Many people are quarantined and staying at home because of a pandemic. Therefore the research and development of the air quality monitoring systems for domestic, industrial, and municipal use are relevant. Air quality monitoring systems` data collection and processing are also actual. This work aims to develop a budget intuitive integrated Internet of Things (IoT) system "Smart House". The IoT system for monitor air quality and control its parameters has been designed.

The analysis of scientific-technical information, design, hardware, and software development of IoT "Smart House" system and an appropriate web application has been done to achieve this goal. Mathematical modeling, system programming, computer and microprocessor architecture, robotics, and methods of computer systems communication have been used. The integrated IoT system evaluates and analyzes the node for measuring the parameters of the environment in the room and the rules of fuzzy control according to experimental data, conducts a questionnaire to summarize the work.

The main focus of the research has been on system integration, the ability to connect a large number of sensors, air quality control, and effective control of load devices in the room so that people can feel comfortable in the room. The IoT system analyzes the data about the environment indoors and outdoors using a certain algorithm. And it determines the node for measurement, using the minimum change and the minimum mean deviation. This algorithm allows us to stabilize the system management, to reduce the impact of erroneous or pseudo-erroneous data, etc. The functionality of the Smart House system allows to ensure indoor comfort and safety, to increase its energy efficiency and simplify the management of various householding automated control systems. In the future, it is going to improve the system by creating a more user-friendly interface, improving algorithms, expanding the functionality of the system, and in-depth study of the measuring and controlling air quality parameters process.