Accurately predicting the concentration of fine particulate matter (PM 2.5) is crucial for
evaluating air pollution levels and public exposure. Recent advancements have seen a …

Recently, researchers have prioritized the accurate forecasting of the particulate matter (PM)
air quality indicators PM 2.5 and PM 10 in urban and industrial locations due to their …

This paper discusses using unsupervised learning in classifying particle-like dispersion. The
problem is relevant to various applications, including virus transmission and atmospheric …

Increase in technologies around the world requires adding intelligence to the objects, and
making it a smart object in an environment leads to the Social Internet of Things (SIoT) …

World is moving towards preceding generation Alpha that believes in socializing the objects
or devices within the network known as Social Internet of Things (SIoT). In SIoT the services …

Smart Environment refers to environment where pollution is detected, predicted, classified
and solved using smart tools and technology such as using Internet of Things (IoT) sensors …

Abstract Machine Learning (ML) significantly drives the advancement of smart cities. This
survey, using databases like IEEE Explorer, Web of Sciences, and Google Scholar …

The phenomena of urbanization is multi-faceted and impacts numerous societal domains
such as infrastructure, environment, and quality of life. Assessing urbanization's quality is …

Researchers are interested in develo** techniques to monitor, manage and predict the
risks of gases and particles emitted from cement factories, which have a direct and negative …

A city becomes a smart city when it employs ICT (information and communication
technology) to share data with the public, improve government services' quality, and develop …