ISSN TBA
Journal of Big Data in Engineering and Design
The Journal of Big Data in Engineering and Design (JBED) is an international, peer-reviewed academic journal dedicated to advancing interdisciplinary research on the application of big data analytics, artificial intelligence, and data-driven technologies in engineering and design. The journal provides a platform for scholars, engineers, and designers to disseminate original theoretical and empirical studies that address complex engineering challenges and design innovations through data-driven approaches. JBED aims to bridge the gap between data science and engineering practice, promoting smart, sustainable, and resilient solutions across diverse sectors.
JBED welcomes original research articles, review papers, and case studies. The journal's scope encompasses, but is not limited to:
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Big Data Analytics in Engineering: Predictive maintenance, structural health monitoring, and data-driven optimization in civil, mechanical, and industrial engineering.
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Data-Driven Design and Innovation: Generative design, parametric modeling, AI-assisted design processes, and digital twins.
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Smart Infrastructure and Urban Systems: Big data applications in smart cities, transportation networks, and building information modeling (BIM).
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Machine Learning and AI in Engineering: Deep learning, computer vision, and intelligent decision-making systems for engineering applications.
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Data Management and Visualization: Engineering data integration, visualization techniques, and decision-support systems.
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Sustainability and Resilience: Big data for energy efficiency, sustainable design, and disaster resilience in engineering systems.
