Integrating ChatGPT, Bard, and leading-edge generative artificial intelligence in building and construction industry: applications, framework, challenges, and future scope

SSRN Electronic Journal, Год журнала: 2023, Номер unknown

Опубликована: Янв. 1, 2023

The infusion of generative artificial intelligence (AI), as exemplified by models such ChatGPT and Bard is proving to be a revolutionary catalyst within the building construction sector. This exploration delves into myriad applications, establishes conceptual framework, confronts challenges, delineates prospective trajectory harnessing AI across diverse stages lifecycle. In domain project management scheduling, contribute optimal resource allocation, task sequencing, timeline optimization, thereby elevating overall efficiency delivery. Design optimization equally pivotal, assists architects engineers in crafting innovative designs that concurrently adhere functional aesthetic criteria. predictive prowess fortifies risk management, furnishing stakeholders with insights potential risks effective mitigation strategies. Meanwhile, realm cost estimation budgeting, enhanced accuracy speed offered optimize financial planning allocation. Supply chain benefits from streamlined processes driven insights, ensuring timely cost-effective procurement materials. Generative linchpin quality control, identifying defects deviations standards enhance quality. Real-time data analysis strengthens site monitoring safety protocols, enabling proactive secure working environment. Collaboration communication teams are augmented AI, facilitating seamless information exchange decision-making processes. Predictive maintenance asset undergo transformation, algorithms predicting equipment failures optimizing schedules. Furthermore, integration tackles imperative energy sustainability Models like bard significantly for conservation sustainable practices. paper also explores incorporation reality (AR), virtual (VR), Building Information Modeling (BIM). Ethical concerns, privacy, robust cybersecurity measures necessitate careful consideration. As industry embraces these innovations, substantial improvements efficiency, sustainability, outcomes poised unfold.

Язык: Английский

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Enhancing lithium-ion battery performance with emerging electrolyte materials for sustainable energy storage solutions: a comprehensive review and prospects

SSRN Electronic Journal, Год журнала: 2023, Номер unknown

Опубликована: Янв. 1, 2023

The swift expansion of renewable energy sources and the growing demand for electric vehicles have spurred intensive research into advancing storage technologies, with a primary focus on lithium-ion batteries (LIBs). This all-encompassing examination delves possibilities offered by emerging electrolyte materials to elevate LIB performance, tackling key obstacles offering insights sustainable solutions. analysis provides thorough exploration recent progress in their impact LIBs, shedding light electrochemical properties, safety considerations, scalability. review most innovations formulations, encompassing ionic liquids, solid-state electrolytes, gel polymer each exhibiting promising attributes such as heightened thermal stability, enhanced profiles, increased density. incorporation these novel has potential address longstanding issues associated conventional liquid including flammability limited cycle life. Various pertinent technologies are discussed within context advancements. Notable breakthroughs involve use liquid-based electrolytes improve stability safety, eliminate flammable components, mechanical strength flexibility. Additionally, explores integration nanomaterials additives optimize addressing challenges related ion transport electrode-electrolyte interfaces. Moreover, scrutinizes implications sustainability, considering factors resource availability, recyclability, environmental impact. widespread adoption commercial applications is examined, emphasizing significance scalability, cost-effectiveness, regulatory considerations. By crucial performance aspects, advancements pave way solutions transition towards cleaner more energy-efficient future.

Язык: Английский

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Leading-edge Artificial Intelligence (AI) and Internet of Things (IoT) technologies for enhanced geotechnical site characterization

SSRN Electronic Journal, Год журнала: 2023, Номер unknown

Опубликована: Янв. 1, 2023

Geotechnical site characterization is a crucial factor in the effective planning, design, and implementation of civil engineering projects. In evolving landscape infrastructure development, integration advanced technologies such as Artificial Intelligence (AI) Internet Things (IoT) has emerged transformative strategy to improve precision efficiency geotechnical processes. This article delves into combined application AI IoT characterization, encompassing diverse range technologies, models, tools, frameworks. AI, utilizing its machine learning algorithms, capacity analyse extensive geospatial geological data, facilitating more accurate identification subsurface conditions. Neural networks deep models play role examining features, predicting soil behaviour, evaluating potential risks associated with construction conjunction incorporation enables real-time monitoring data acquisition at sites. Ground-embedded sensor gather geophysical including moisture, temperature, pressure, providing dynamic continuous understanding feeds creating feedback loop that refines predictions enhances characterization. Moreover, introduces various tools frameworks facilitate seamless engineering. Geographic Information Systems (GIS) are employed for spatial analysis, aiding visualization interpretation complex data. Additionally, Building Modelling (BIM) explored means integrate information overall project promoting holistic approach planning. Embracing this technological synergy essential addressing challenges modern development ensuring sustainability resilience projects future.

Язык: Английский

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Integrating ChatGPT, Bard, and Leading-Edge Generative Artificial Intelligence in Architectural Design and Engineering: Applications, Framework, and Challenges

International Journal of Architecture and Planning, Год журнала: 2023, Номер 3(2), С. 92 - 124

Опубликована: Сен. 5, 2023

This research paper investigates the integration of advanced generative artificial intelligence (AI) models, such as ChatGPT, Bard, and similar architectures, in architectural design engineering.The comprehensive study explores various aspects, including applications, frameworks, challenges, prospective developments context engineering.In design, transformative impact on Architectural Theory, highlighting how AI fosters creativity innovation thinking.The Design Process is scrutinized, showcasing models streamline ideation, iteration, collaboration among teams.Furthermore, examines influence Interior Design, Urban Planning, considers nuanced aspects Cultural Social factors, elucidating these technologies contribute to inclusive context-sensitive practices.In engineering, assesses Structural Engineering, demonstrating its potential optimize innovate structural analysis designs for enhanced safety efficiency.It applications Building Systems Construction Management, illustrating can project workflows resource allocation.The compliance with Codes Regulations analyzed, emphasizing error reduction adherence standards.Additionally, probes into Materials Technology, advancements material selection construction methodologies.The also role promoting Sustainability Environmental energy efficiency, reduce environmental impact, enhance overall sustainability.Finally, outlines challenges future directions development fully harness shaping engineering.

Язык: Английский

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Modeling Teachers’ Acceptance of Generative Artificial Intelligence Use in Higher Education: The Role of AI Literacy, Intelligent TPACK, and Perceived Trust

Education Sciences, Год журнала: 2024, Номер 14(11), С. 1209 - 1209

Опубликована: Ноя. 3, 2024

This study delves into the factors that drive teachers’ adoption of generative artificial intelligence (GenAI) technologies in higher education. Anchored by technology acceptance model (TAM), research expands its inquiry integrating constructs intelligent technological pedagogical content knowledge (TPACK), AI literacy, and perceived trust. Data were gathered from a sample 237 university teachers through structured questionnaire. The employed structural equation modeling (SEM) to determine relationships among constructs. results revealed both literacy ease most influential affecting GenAI. Notably, TPACK trust found be pivotal mediators this relationship. findings underscore importance fostering adapting frameworks better equip educators age AI. Furthermore, there is clear need for targeted professional development initiatives focusing on practical training enhances literacy. These programs should provide hands-on experience with GenAI tools, boosting educators’ confidence ability integrate them their teaching practices.

Язык: Английский

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