Advancements in AI-Based Anomaly Detection for Smart Manufacturing

Springer series in advanced manufacturing, Journal Year: 2025, Volume and Issue: unknown, P. 37 - 68

Published: Jan. 1, 2025

Language: Английский

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Enhancing structural health monitoring with AI-ML algorithms: a focus on crack detection and prediction

Asian Journal of Civil Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 4, 2025

Language: Английский

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Towards Sustainable Intelligence

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 203 - 228

Published: April 17, 2025

As cloud computing grows, so does the environmental impact of data centres, with energy use and electronic waste emerging as key concerns. This paper tends to understand how combining green intelligent engineering practices can help build more sustainable infrastructure. Focusing on two main areas, such optimization e-waste reduction. It analyses AI-driven approaches like resource allocation predictive maintenance make a difference. In practice, leverages machine learning handle workloads efficiently, adjusting resources based real-time demand. approach not only reduces excess but also cuts down carbon emissions. Meanwhile, taps into analytics monitor hardware health, addressing potential issues before they turn failures. proactive extends lifespan minimizes e-waste, reducing need for frequent replacements.

Language: Английский

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ML2MAS: A Multi-Agent Reinforcement Learning and BNNs-GAN Integration Framework for Smart Manufacturing Optimization

Published: Jan. 1, 2024

Language: Английский

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Harnessing Industry 4.0: A Framework for Integrating AI and Emerging Technologies

Published: Sept. 28, 2024

Language: Английский

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