American International Journal of Research and Innovation

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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Industrial Internet of Things Applications for Operational Excellence

Author(s) Elmer Jose P. Dadios
Country Philippines
Abstract The Industrial Internet of Things (IIoT) has emerged as a transformative technology for improving operational excellence by enabling intelligent connectivity, real-time monitoring, data-driven decision-making, and process optimization in industrial environments. The increasing demand for efficient production systems, reduced operational costs, improved asset performance, and enhanced industrial competitiveness has accelerated the adoption of IIoT-based solutions. This conceptual research article examines Industrial Internet of Things applications and their contribution toward achieving operational excellence across modern industrial systems.
The study explores the role of connected sensors, edge computing, artificial intelligence, cloud platforms, industrial analytics, and smart automation in improving operational efficiency. A conceptual research methodology is adopted through the analysis of existing scholarly literature, Industry 4.0 frameworks, digital transformation models, and industrial technology approaches.
The findings indicate that IIoT applications provide significant benefits through predictive monitoring, optimized resource utilization, improved productivity, enhanced quality management, and intelligent operational control. However, challenges related to cybersecurity, data management, infrastructure requirements, interoperability, and workforce capabilities remain important barriers. The study concludes that IIoT represents a critical foundation for future industrial excellence by integrating digital intelligence with connected and adaptive operational systems.
Keywords Industrial Internet of Things; Operational Excellence; Industry 4.0; Smart Manufacturing; Industrial Analytics; Edge Computing; Digital Transformation.
Field Engineering
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-06-30

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