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Segmentation of LiDAR point cloud data in urban areas using adaptive neighborhood selection technique.

PloS one
Semantic segmentation of urban areas using Light Detection and Ranging (LiDAR) point cloud data is challenging due to the complexity, outliers, and heterogeneous nature of the input point cloud data. The machine learning-based methods for segmenting ...

MSW-Net: A hierarchical stacking model for automated municipal solid waste classification.

Journal of the Air & Waste Management Association (1995)
Efficient solid waste management is crucial for urban health and welfare in the midst of fast industrialization and urbanization. In this changing environment, government authorities have a significant role in addressing and reducing the effects of s...

Integrating deep learning and regression models for accurate prediction of groundwater fluoride contamination in old city in Bitlis province, Eastern Anatolia Region, Türkiye.

Environmental science and pollution research international
Groundwater resources in Bitlis province and its surroundings in Türkiye's Eastern Anatolia Region are pivotal for drinking water, yet they face a significant threat from fluoride contamination, compounded by the region's volcanic rock structure. To ...

Designing energy-efficient buildings in urban centers through machine learning and enhanced clean water managements.

Environmental research
Rainwater Harvesting (RWH) is increasingly recognized as a vital sustainable practice in urban environments, aimed at enhancing water conservation and reducing energy consumption. This study introduces an innovative integration of nano-composite mate...

Quantification of litter in cities using a smartphone application and citizen science in conjunction with deep learning-based image processing.

Waste management (New York, N.Y.)
Cities are a major source of litter pollution. Determination of the abundance and composition of plastic litter in cities is imperative for effective pollution management, environmental protection, and sustainable urban development. Therefore, here, ...

Prediction of developmental toxic effects of fine particulate matter (PM) water-soluble components via machine learning through observation of PM from diverse urban areas.

The Science of the total environment
The global health implications of fine particulate matter (PM) underscore the imperative need for research into its toxicity and chemical composition. In this study, zebrafish embryos exposed to the water-soluble components of PM from two cities (Har...

Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HEAT Center study protocol.

BMJ open
INTRODUCTION: African cities, particularly Abidjan and Johannesburg, face challenges of rapid urban growth, informality and strained health services, compounded by increasing temperatures due to climate change. This study aims to understand the compl...

Urban environmental monitoring and health risk assessment introducing a fuzzy intelligent computing model.

Frontiers in public health
INTRODUCTION: To enhance the precision of evaluating the impact of urban environments on resident health, this study introduces a novel fuzzy intelligent computing model designed to address health risk concerns using multi-media environmental monitor...

Identification of biological indicators for human exposure toxicology in smart cities based on public health data and deep learning.

Frontiers in public health
With the acceleration of urbanization, the risk of urban population exposure to environmental pollutants is increasing. Protecting public health is the top priority in the construction of smart cities. The purpose of this study is to propose a method...

Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies.

BMC medical imaging
The quick proliferation of pandemic diseases has been imposing many concerns on the international health infrastructure. To combat pandemic diseases in smart cities, Artificial Intelligence of Things (AIoT) technology, based on the integration of art...