Efficiency of Neo4j in Designing and Analysing Graph Database for Air Quality Analysis of Indian Metro Cities
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Abstract
The analysis of the Air Quality Index (AQI) is currently a popular subject in the area of sustainable research, as it is crucial for investigating and analysing the effects of air pollutants on human health in urban environments. It has been identified over the last decade that airborne pollution has become a critical issue and will remain an important concern in India in the coming years. In recent years, a variety of models and algorithms utilizing big data techniques have been developed for the analysis of air quality data. In this paper, we suggest monitoring and feature analysis of air quality data using a graph database. The research aims to analyse the annual and seasonal variations of AQI over a 10-year period between 2015–2024 from daily averaged concentration data of key air pollutants for 5 metro cities of India. The trends shown by all the cities have been compared to understand the seasonal variations in the average Air quality index. The variations of Average AQI in different severity classes in the cities also provide in-depth analysis of the trends. The findings from this analysis yield highly valuable information to assist in air pollution control, consequently leading to substantial societal and technical impacts. Finally, we offer a perspective on the future of air quality analysis, presenting some promising and challenging concepts. The results of this study can promote a more effectual environment monitoring system to detect drastic or unusual changes in atmosphere through the use of modern technologies.
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