Smart and Sustainable Built Environment (SSBE)

Smart and Sustainable Built Environment is a CIB-encouraged journal that aims to inform research and industry practice on integrated approaches to developing smart and sustainable built environments Smart and Sustainable Built Environment (SASBE) links together the various pioneering smart and sustainable targets, bottom lines, endpoints and project deliverables through the whole development cycles and project processes. The objective of the journal is to identify, develop, and promote research and practice in the integration of innovation and sustainability in order to help the AEC industry go through a smooth transition and paradigm shift. The journal highlights holistic problem-solving and decision-making, collaborative system and product development, innovative solutions enhancing sustainability, and mutually beneficial outcomes for all stakeholders of the built environment. It also emphasises international collaboration, inclusivity, emerging challenges, issues arising from developing economies, and knowledge transfer to businesses and industries. Advanced Simulation, Computer Vision, Internet of Things (IoT), Blockchain, Machine Learning, Deep Learning, and Linked Data all provide immense opportunities for dealing with these challenges; more importantly, perhaps, provide real tangible (evidenced-based) innovative solutions that until now, have never been possible before. These technologies, alongside Large Language Models (LLMs) and Natural Language Processing (NLP), provide unprecedented opportunities to tackle challenges and drive tangible, evidence-based innovations in the built environment. They are perceived as the ‘true’ enablers of future practice. Examples from other industries such as automotive, aerospace, and oil and gas have provided a showcase of solutions using advanced technologies.

Smart and Sustainable Built Environment (SSBE) is :-

• International, Peer-Reviewed, Open Access, Refereed, Sustainable Architecture, Construction Engineering, Building Information Modeling, Digital Twins, Internet of Things, Machine Learning, Artificial Intelligence, Civil Engineering, Project Management, Environmental Design , Online or Print , Bi-Monthly Journal

• UGC Approved, ISSN Approved: P-ISSN P-ISSN: 2046-6099, E-ISSN: 2046-6102, Established: 2012, Impact Factor: 4.6
• Provides Crossref DOI

• Indexed in: Scopus, WoS

• Not indexed in DOAJ, PubMed, UGC CARE