Studies in computational intelligence, Journal Year: 2024, Volume and Issue: unknown, P. 329 - 342
Published: Jan. 1, 2024
Language: Английский
Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11934 - 11934
Published: Dec. 20, 2024
The integration of Artificial Intelligence (AI) and smart technologies into safety management is a pivotal aspect the Fourth Industrial Revolution or Industry 4.0. This study conducts systematic literature review to identify analyze how AI enhance across various sectors within Safety 4.0 paradigm. Focusing on peer-reviewed journal articles that explicitly mention “Smart”, “AI”, “Artificial Intelligence” in their titles, research examines key factors, such as accident prevention, risk management, real-time monitoring, ethical implementation, sectors, including construction, industrial safety, disaster public transport logistics, energy power, health, home living, other diverse industries. AI-driven solutions, predictive analytics, machine learning algorithms, IoT sensor integration, digital twin models, are shown proactively mitigate potential hazards, optimize consumption, operational efficiency. For instance, power sector, intelligent gas meters automated fire suppression systems manage gas-related risks effectively, while health AI-powered monitoring devices mental support applications improve patient worker safety. analysis reveals significant trend towards shifting from reactive proactive facilitated by convergence with Big Data analytics. Additionally, considerations data privacy emerge critical challenges adoption technologies. highlights transformative role enhancing protocols, reducing rates, improving overall outcomes It underscores need for standardized robust governance frameworks, interdisciplinary address existing maximize benefits management. Future directions include developing explainable human–AI collaboration, fostering global standardization ensure responsible effective implementation solutions.
Language: Английский
Citations
4
SSRN Electronic Journal, Journal Year: 2023, Volume and Issue: unknown
Published: Jan. 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.
Language: Английский
Citations
10
SSRN Electronic Journal, Journal Year: 2023, Volume and Issue: unknown
Published: Jan. 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.
Language: Английский
Citations
10
Future Internet, Journal Year: 2024, Volume and Issue: 16(7), P. 225 - 225
Published: June 27, 2024
Modern building automation systems implement plenty of advanced control and monitoring functions that consider various parameters like users’ activity, lighting, temperature changes, etc. Moreover, novel solutions based on the Internet Things cloud services are also being developed for smart buildings to ensure comfort use, user safety, energy efficiency improvements, integration with grids city platforms. Such a wide spectrum technologies requires approach in design provide effective implementation flexibility during operation. At same time, operation industries, tools information modeling digital twins developed. This paper discusses development directions application areas these solutions, identifying new trends possibilities their use homes buildings. In particular, focus is procedures selecting functions, integration, interoperability management Things, considering organization prediction mechanisms dynamic functional changes networks. Chosen should requirements set out EN ISO 52120 standard guidelines defined Smart Readiness Indicator.
Language: Английский
Citations
3
Studies in computational intelligence, Journal Year: 2024, Volume and Issue: unknown, P. 329 - 342
Published: Jan. 1, 2024
Language: Английский
Citations
3