Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108484 - 108484
Published: April 1, 2025
Language: Английский
Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108484 - 108484
Published: April 1, 2025
Language: Английский
Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 112422 - 112422
Published: March 1, 2025
Language: Английский
Citations
0Sustainability, Journal Year: 2025, Volume and Issue: 17(9), P. 4134 - 4134
Published: May 2, 2025
The growing energy demands and increasing environmental concerns in industrial manufacturing necessitate innovative solutions to reduce fuel consumption lower carbon emissions. This paper presents Sustain AI, a multi-modal deep learning framework that integrates Convolutional Neural Networks (CNNs) for defect detection, Recurrent (RNNs) predictive modeling, Reinforcement Learning (RL) dynamic optimization enhance sustainability. employs IoT-based real-time monitoring AI-driven supply chain optimize use. Experimental results demonstrate AI achieves an 18.75% reduction 20% decrease CO2 emissions through processes scheduling optimizations. Additionally, waste heat recovery efficiency improved by 25%, smart HVAC systems reduced 18%. CNN-based detection model enhanced material identification accuracy 42.8%, leading production efficiency. proposed also ensures economic feasibility, with 17.2% operational costs. is scalable, adaptable, fully compatible Industry 4.0 requirements, making it viable solution sustainable practices. Future extensions include enhancing adaptive decision-making RL techniques incorporating blockchain-based traceability secure transparent management. These findings indicate AI-powered ecosystems can achieve neutrality intelligent strategies.
Language: Английский
Citations
0Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108484 - 108484
Published: April 1, 2025
Language: Английский
Citations
0