Mapping the Scientific Landscape of Smart Buildings and Climate Change

Abstract

The purpose of this paper is to conduct a comprehensive data mining, analysis, and visualization of smart cities and climate change, with a focus on development, trends, active actors, and the interrelationship between countries and active institutions. The study is based on the Scopus database and the Visualization Of Similarities Method (VOS) method between objects. Results revealed that 1653 articles were published since 1997, but 97% of these articles were published in the last 10 years alone. The top five most active countries are the USA, India, UK, Italy, and China. 20% of the total documents were in engineering, 16% in environmental science, 14% in social sciences, 12% in computer science, and 12% in energy. The overly visualization revealed that recent publications are more focused on smart cities, climate change, and energy storage with the application of AI, machine learning, deep learning, IoT, and sensors. This study shows how important it is to map the scientific landscape of smart buildings and climate change, which has unveiled an increase in research and provide a valuable tool for finding practical ways to build smart cities while fighting climate change and protecting the environment.