Civil Engineering Science and Technology (CEST)
Aim The Civil Engineering Science and Technology (CEST) journal aims to serve as a high-quality scientific publication platform dedicated to the field of civil engineering. The journal focuses on the scientific and technological aspects that contribute to the advancement of methods, materials, and innovations in civil engineering. CEST facilitates the dissemination of cutting-edge research findings that enhance both theoretical understanding and practical applications in the civil engineering industry. By providing a forum for academics, researchers, and practitioners, the journal encourages interdisciplinary collaboration and fosters global advancements in civil engineering science and technology. Scope CEST covers a broad range of topics within civil engineering, including but not limited to: Soil and Rock Mechanics – Studies on geotechnical properties, foundation engineering, slope stability, and soil-structure interactions. Structures and Materials – Research on structural analysis, construction materials, seismic engineering, and innovative building techniques. Hydraulic and Hydrology – Water resources management, fluid mechanics, river engineering, and coastal protection systems. Transportation and Infrastructure – Roadway and railway engineering, traffic management, urban mobility, and smart transportation systems. Environment and Resource Management – Sustainable construction, waste management, climate resilience, and eco-friendly engineering solutions. Information and Computing Technology in Civil Engineering – Applications of AI, BIM (Building Information Modeling), GIS, and digital twin technology in civil engineering. Innovation and Technological Development in Civil Engineering – Emerging trends, automation, robotics, and new methodologies for construction and infrastructure development. Case Studies and Practical Applications – Real-world civil engineering projects, lessons learned, and best practices in various construction domains. By covering these diverse areas, CEST aims to bridge the gap between research and industry, fostering technological innovation and sustainable development in civil engineering.
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"Vol. 1 No. 2 (2025): October | CEST (Civil Engineering Science and Technology)"
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<![CDATA[Integrating Predictive AI Models to Bridge Energy Efficiency Gaps in Smart Building Design ]]>
<![CDATA[Sugiarto, Sugiarto]]>;
<![CDATA[Christopher, Liam]]>;
<![CDATA[Grace, Amelia]]>
<![CDATA[ Civil Engineering Science and Technology Vol. 1 No. 2 (2025): October | CEST (Civil Engineering Science and Technology) ]]>
Publisher : <![CDATA[Universitas Sains dan Teknologi Komputer ]]>
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DOI: 10.51903/2fwp7m63
<![CDATA[Energy efficiency has become one of the most important aspects in smart building design, especially considering the gap that has increasingly been noted between simulated energy performance and actual consumption. Even though digital design tools like BIM have enhanced design capabilities, there is still a big gap in energy performance, usually rooted in the static nature of traditional simulations. This research tries to respond to this challenge by proposing a conceptual framework linking predictive AI models with BIM for enhanced accuracy in early design stage forecasting. Other than a few studies that revolved around optimization in the post-occupancy phase, this study applies a conceptual-simulative methodology by using a synthetic BIM model of a medium-sized office building. Machine learning algorithms, such as random forest and gradient boosting, were trained on parameterized design data for predicting EUI. Strong predictive consistency was identified with an R² of 0.89 between the predicted and simulated EUI and a conceptual reduction of the performance gap of about 18%. The model also shows robust logical correspondence to the concepts of energy efficiency within a wide range of design scenarios. This research concludes that predictive AI can significantly improve energy performance forecasting in smart building design and provides a proactive data-driven approach toward overcoming the energy efficiency gap in support of more sustainable architectural practices without immediate physical field testing.]]>
