Data-Driven Smart Sustainable Cities: Advanced Solutions for Environmental Sustainability

Dear colleague,

This Special Issue intends to stimulate in-depth research and discussion on the advanced solutions for environmental sustainability in the context of data-driven smart sustainable cities. The concentration of economic activities, the high-intensity use of resources, and the massive deployment of non-renewable energy in cities demonstrate that they have major negative impacts on the environment. In the current climate of the unprecedented urbanization of the world, it is becoming increasingly more challenging for both smart cities and sustainable cities to configure themselves more sustainably and efficiently from an environmental perspective. Indeed, urban growth raises a variety of problems that jeopardize the environmental sustainability of modern cities, as it puts an enormous strain on urban systems and thus great demand on energy resources.

Currently, greater importance is given to economic development and social development at the cost of environmental protection. In recent years, major topics discussed in the area of environmental sustainability have included the depletion of non-renewable resources, the harvesting of renewable resources, the destruction of ecosystems, and the generation of pollution, as well as the role of advanced ICT in tackling environmental problems through innovative control and monitoring systems. With respect to the latter, computational data analytics approaches are being extensively used to observe and discover hidden patterns of energy production and consumption in order to devise more effective solutions that could avert the multidimensional effects of devouring energy on the environment. There is a general consensus that innovative data-driven technology solutions hold great potential to improve energy efficiency and mitigate climate change. This is at the core of the vision of smart energy, which aims to achieve energy systems that are highly efficient, increasingly powered by renewable and local energy sources enabled by new technologies, and less dependent on fossil fuels. This vision has spurred the development of new approaches to future sustainable energy systems, such as smart grids, automated metering infrastructure, smart buildings, integrated renewable solutions, solar photovoltaic panels, and so on.

In light of the above, we can make a positive impact on the environment by making smart cities more sustainable and sustainable cities smarter in terms of their energy and environmental efficiency. In particular, the recent advances in the IoT, big data analytics, and Artificial Intelligence, coupled with higher-level urban computing and intelligence infrastructure, have offered many new opportunities to develop and use new urban intelligence and planning functions for energy efficiency, pollution reduction, and urban metabolism. Therefore, these emerging technologies have become essential to the functioning of both smart cities and sustainable cities with respect to environmental sustainability.

This Special Issue of Smart Cities is devoted to promoting the investigation of the latest data-driven technologies and applied solutions offered by smart cities for advancing sustainable cities in terms of their contribution to the goals of environmental sustainability. And more importantly for integrating their strategies and solutions within the framework of data-smart sustainable cities.This Special Issue seeks contributions—in the form of research articles, literature reviews, case reports, futures studies, short communications, project reports, and discussion papers—that offer insights into data-driven smart sustainable urbanism. The scope of this Special Issue includes, but is not limited to, the following broad topics:

• Data-driven smart cities and environmental sustainability;
• Sustainable cities and data-driven environmental technologies;
• Environmental challenges for smart cities and sustainable cities;
• The role of data-driven urban analytics in environmental sustainability;
• Data-driven solutions for smart grids and automated metering infrastructure;
• Data-driven solutions for smart environmental monitoring;
• Data-driven smart solutions for sustainable transportation;
• Data-driven solutions for smart transport and traffic;
• Data-driven solutions for smart mobility and parking;
• Data-driven solutions for smart buildings and homes;
• Data-driven solutions for smart street lighting infrastructure;
• Data-driven solutions for urban infrastructure management;
• Data-driven smart solutions for sustainable energy;
• Data-driven smart solutions for sustainable waste management;
• Data-driven smart solutions for urban metabolism models;
• Integrated renewable solutions based on big data analytics;
• Practical examples and best practice insights in smart energy and smart environment;
• Urban intelligence functions for smart energy and smart environment;
• IoT- and AI-enabled energy systems for smart sustainable cities;
• Data-driven smart environmental planning and climate policy.

Dr. Simon Elias Bibri
Guest Editor