In recent years, low-cost air pollution technologies have gained increasing interest and,
have been studied widely by the scientific community. Thus, these new sensing …

Air pollution is a global geo-hazard with significant implications, including deterioration of
health and premature death. Climatic variables such as temperature, rainfall, wind, and …

This study presents a new strategy to predict the monthly groundwater level with short-and
long-lead times over the Rafsanjan aquifer in Iran using an ensemble machine learning …

With the increase in population and industrialization, air pollution has become one of the
global problems nowadays. Therefore, air pollutant parameters should be measured at …

Low-cost sensors (LCS) can construct a high spatial and temporal resolution PM 2.5 network
but are affected by environmental parameters such as relative humidity and temperature …

Over the past decade, there has been exponential growth in low-cost air pollution sensing
technology. While low-cost sensors can provide a path towards more accessible air quality …

Ensemble machine learning models have been widely used in hydro-systems modeling as
robust prediction tools that combine multiple decision trees. In this study, three newly …

Air pollution has a major impact on human health, especially in cities, and elevated
concentrations of PMx are responsible for a large number of premature deaths each year …

The increasing use of low-cost sensors in monitoring the surrounding environment requires
efficient handling of sensor drift and sensor errors. Therefore, there is a pressing need to …

IoT sensors are becoming increasingly important supplement to traditional monitoring
systems, particularly for in-situ based monitoring. Data collected using IoT sensors are often …