Combining Green Metrics and Digital Twins for Sustainability Planning and Governance of Smart Buildings and Cities

Creating a more sustainable world will require a coordinated effort to address the rise of social, economic, and environmental concerns resulting from the continuous growth of cities. Supporting planners with tools to address them is pivotal, and sustainability is one of the main objectives. Modeling and simulation augmenting digital twins can play an important role to implement these tools. Although various green best practices have been utilized over time and there are related attempts at measuring green success, works in the published literature tend to focus on addressing a single problem (e.g., energy efficiency), and a comprehensive approach that takes the multiple facets of sustainable urban planning into consideration has not yet been identified. This paper begins with a review of recent research efforts in green metrics and digital twins. This leads to developing an approach that evaluates organizational green best practices to derive metrics, which are used for computational decision support by digital twins. Furthermore, it leverages these research results and proposes a metric-driven framework for sustainability planning that understands a city as a sociotechnical complex system. Such a framework allows the practitioner to take advantage of recent developments and provides computational decision support for the complex challenge of sustainability planning at the various levels of urban planning and governance

Trends in Smart City Development

This report examines the meanings and practices associated with the term 'smart cities.' Smart city initiatives involve three components: information and communication technologies (ICTs) that generate and aggregate data; analytical tools which convert that data into usable information; and organizational structures that encourage collaboration, innovation, and the application of that information to solve public problems

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Participatory sensing as an enabler for self-organisation in future cellular networks

In this short review paper we summarise the emerging challenges in the field of participatory sensing for the self-organisation of the next generation of wireless cellular networks. We identify the potential of participatory sensing in enabling the self-organisation, deployment optimisation and radio resource management of wireless cellular networks. We also highlight how this approach can meet the future goals for the next generation of cellular system in terms of infrastructure sharing, management of multiple radio access techniques, flexible usage of spectrum and efficient management of very small data cells