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Spatial and deep learning analyses of urban recovery from the impacts of COVID-19.

Scientific reports
This study investigates urban recovery from the COVID-19 pandemic by focusing on three main types of working, commercial, and night-life activities and associating them with land use and inherent socio-economic patterns as well as points of interests...

A hybrid deep learning framework for air quality prediction with spatial autocorrelation during the COVID-19 pandemic.

Scientific reports
China implemented a strict lockdown policy to prevent the spread of COVID-19 in the worst-affected regions, including Wuhan and Shanghai. This study aims to investigate impact of these lockdowns on air quality index (AQI) using a deep learning framew...

Point Cloud Deep Learning Network Based on Balanced Sampling and Hybrid Pooling.

Sensors (Basel, Switzerland)
The automatic semantic segmentation of point cloud data is important for applications in the fields of machine vision, virtual reality, and smart cities. The processing capability of the point cloud segmentation method with PointNet++ as the baseline...

Uncertainty and sensitivity analysis of deep learning models for diurnal temperature range (DTR) forecasting over five Indian cities.

Environmental monitoring and assessment
In this article, the maximum and minimum daily temperature data for Indian cities were tested, together with the predicted diurnal temperature range (DTR) for monthly time horizons. RClimDex, a user interface for extreme computing indices, was used t...

Research on the development trend, evolution, and spatial local characteristics of the intelligent smart medical industry in the Yangtze River Economic Belt.

Frontiers in public health
A comprehensive survey of the development trends, trend evolution, and spatial non-equilibrium characteristics of the intelligent smart medical industry in the Yangtze River Economic Belt could provide significant policy implications for optimizing t...

Towards low-carbon development: The role of industrial robots in decarbonization in Chinese cities.

Journal of environmental management
Technological advancements have played a key role in improving energy efficiency and reducing emissions, and industrial robots are important carriers of intelligent manufacturing and industrial upgrading. Although various countries and regions are un...

Assessing the Role of AI-Based Smart Sensors in Smart Cities Using AHP and MOORA.

Sensors (Basel, Switzerland)
We know that in today's advanced world, artificial intelligence (AI) and machine learning (ML)-grounded methodologies are playing a very optimistic role in performing difficult and time-consuming activities very conveniently and quickly. However, for...

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning.

Sensors (Basel, Switzerland)
Due to the increasing urban development, it has become important for municipalities to permanently understand land use and ecological processes, and make cities smart and sustainable by implementing technological tools for land monitoring. An importa...

Urban Heat Island Intensity Changes in Guangdong-Hong Kong-Macao Greater Bay Area of China Revealed by Downscaling MODIS LST with Deep Learning.

International journal of environmental research and public health
The urban heat island (UHI) effect caused by urbanization negatively impacts the ecological environment and human health. It is crucial for urban planning and social development to monitor the urban heat island effect and study its mechanism. Due to ...

Forecasting the Status of Municipal Waste in Smart Bins Using Deep Learning.

International journal of environmental research and public health
The immense growth of the population generates a polluted environment that must be managed to ensure environmental sustainability, versatility and efficiency in our everyday lives. Particularly, the municipality is unable to cope with the increase in...