AIMC Topic: Sustainable Development

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Can " Zero waste city" policy promote green technology? Evidence from econometrics and machine learning.

Journal of environmental management
The promotion of green technology innovation (GTI) is regarded as an effective way to protect the environment and achieve sustainable development. The "Zero waste city" construction pilot policy (ZWCP), is an important policy for the promotion of was...

Digital brains, green gains: Artificial intelligence's path to sustainable transformation.

Journal of environmental management
The environmental impacts of artificial intelligence on a global scale remain underexplored. This study utilizes a balanced panel dataset to examine artificial intelligence's complex role in enhancing global green productivity between 2008 and 2019. ...

An empirical study for mitigating sustainable cloud computing challenges using ISM-ANN.

PloS one
The significance of cloud computing methods in everyday life is growing as a result of the exponential advancement and refinement of artificial technology. As cloud computing makes more progress, it will bring with it new opportunities and threats th...

Integrating multisource data and machine learning for supraglacial lake detection: Implications for environmental management and sustainable development goals in high mountainous regions.

Journal of environmental management
The accurate detection and monitoring of supraglacial lakes in high mountainous regions are crucial for understanding their dynamic nature and implications for environmental management and sustainable development goals. In this study, we propose a no...

From expansion to efficiency: Machine learning-based forecasting of Japan's building material stocks under demographic declines.

The Science of the total environment
Japan's unique demographic trajectory, marked by population decline and aging, coupled with continued urbanization, presents distinct challenges for aligning built environment capacity with resource efficiency. This study aims to investigate the hist...

Digital innovations for monitoring sustainability in food systems.

Nature food
Monitoring systems that incentivize, track and verify compliance with social and environmental standards are widespread in food systems. In particular, digital monitoring approaches using remote sensing, machine learning, big data, smartphones, platf...

The circular economy through the prism of machine learning and the YouTube video media platform.

Journal of environmental management
The transition to a Circular Economy (CE) is rapidly gaining ground across countries and industries. It is the means of achieving more sustainable development by adopting innovative environmentally friendly strategies and saving primary resources. Th...

Climate change and artificial intelligence in healthcare: Review and recommendations towards a sustainable future.

Diagnostic and interventional imaging
The rapid advancement of artificial intelligence (AI) in healthcare has revolutionized the industry, offering significant improvements in diagnostic accuracy, efficiency, and patient outcomes. However, the increasing adoption of AI systems also raise...

Network science and explainable AI-based life cycle management of sustainability models.

PloS one
Model-based assessment of the potential impacts of variables on the Sustainable Development Goals (SDGs) can bring great additional information about possible policy intervention points. In the context of sustainability planning, machine learning tec...

Machine learning-based surrogate modelling of a robust, sustainable development goal (SDG)-compliant land-use future for Australia at high spatial resolution.

Journal of environmental management
We developed a high-resolution machine learning based surrogate model to identify a robust land-use future for Australia which meets multiple UN Sustainable Development Goals. We compared machine learning models with different architectures to pick t...