The recent advancements made in the realms of Artificial Intelligence (AI) and Artificial
Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to …

In the dynamic landscape of sustainable smart cities, emerging computational technologies
and models are resha** data-driven planning strategies, practices, and approaches …

Artificial intelligence (AI) will transform business practices and industries and has the
potential to address major societal problems, including sustainability. Degradation of the …

Many studies have applied machine learning to crop yield prediction with a focus on specific
case studies. The data and methods they used may not be transferable to other crops and …

Conservation of marine ecosystems has been highlighted as a priority to ensure a
sustainable future. Effective management requires data collection over large spatio-temporal …

Traditional engineering approaches alone (gray infrastructure) are not able to meet all the
challenges of sustainability posed by growing urban population and consumption. Urban …

The circumstances under which different ecosystem service benefits can be realized differ.
The benefits tend to be coproduced and to be enabled by multiple interacting social …

Modeling is essential to characterize and explore complex societal and environmental
issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling …

Over the last 60 years, soil microbiologists have accumulated a wealth of experimental data
showing that the bulk, macroscopic parameters (eg, granulometry, pH, soil organic matter …

Urban areas are expanding due to rural-urban migration and due to population increases.
Their resilience is being challenged due to socio-political consequences of increasingly …