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Improvements in product quality, operational efficiency, maintenance accuracy, and cost reduction are demonstrated, highlighting Digital Twins as a key enabler of smart manufacturing and Industry 4.0.
This study presents a comprehensive research framework for Industry 5.0-oriented human-centric robotic manufacturing systems by integrating collaborative robotics, AI-assisted decision-making, adaptive sensing, real-time monitoring, and intelligent manufacturing analytics.
The importance of Digital Twin as a crucial enabling technology for new generation smart warehouses and for the intelligent supply chain in Industry 5.0 is shown, as well as the opportunities for future research in autonomous logistics operations in Industry 5.0.
By integrating iiot with advanced analytics, smart manufacturing analytics supports the development of intelligent, autonomous, and sustainable manufacturing systems for the next generation of smart factories.
This paper proposes an **Intelligent Human–AI Collaboration Framework for Future Digital Workplaces** consisting of four stages: workplace data integration, intelligent knowledge processing, collaborative decision intelligence, and adaptive feedback optimization.
This paper explores Agentic AI architectures for autonomous business applications, highlighting their role in finance, healthcare, supply chain, enterprise resource planning, customer relationship management, and industrial operations and their importance for successful enterprise adoption.
The study analyzes how platforms reshape industry boundaries, create new forms of market power, and influence the survival of traditional firms as well as highlighting strategies required for sustainable participation in platform-based economies.
An AI-enabled Autonomous Water Distribution System (AWDS) that integrates IoT sensors, edge-cloud computing, and predictive analytics for real-time leak detection and proactive maintenance and provides a scalable and sustainable solution for intelligent water resource management.
This study presents a conceptual framework that combines semantic retrieval, intelligent reasoning, automated literature analysis, and workflow orchestration, demonstrating how LLM-powered systems can transform scientific research into scalable, accurate, ethical, and collaborative knowledge discovery processes.
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