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Abstract Advances in AI have transformed the traditional Internet of Things (IoT) into smarter, more versatile next-generation devices. Enhanced connectivity among sensors, actuators, and appliances boosts data availabil...

Abstract Proposed research presents a data-driven framework for forecasting municipal solid waste (MSW) generation and emission dynamics in Erode City, India, by employing supervised machine learning algorithms. Leveragi...

Abstract The stability of surrounding rock is a critical challenge in underground engineering. Accurate prediction of Excavation Damaged Zone Thickness (EDZT) in surrounding rock is vital for designing safe underground s...

Abstract Land-use change strongly regulates soil physical, chemical, and biogeochemical properties, with major implications for soil organic carbon (SOC) storage in the Brazilian Amazon to a depth of 30 cm. This study a...

Abstract Air pollution, particularly Nitrogen Dioxide ( $$\text {NO}_2$$ ) and ground-level ozone ( $$\text {O}_3$$ ), poses major risks to human health and the environment, making accurate forecasting essential for effe...

Abstract Substantial efforts have been made to modernize and decarbonize the waste collection industry. Smart sensor-based waste collection (SWC) systems have been developed to optimize collection routes based on the act...

Abstract Hybrid Brain–Computer Interface (BCI) systems that combine electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) achieve higher classification accuracy but face computational bottlenec...

Abstract High-throughput analysis of EEG data has significantly contributed to understanding neural dynamics in Alzheimer’s disease diagnosis. However, the complexity and high dimensionality of EEG signals pose challen...