Advancing Process Optimization Through AI-Enhanced Cloud Computing for Real-Time Data Insights

Author(s)	Srinivas Kolluri
Country	United States
Abstract	This comprehensive technical article explores the transformative impact of cloud-native AI solutions on manufacturing operations, focusing particularly on predictive maintenance and process optimization. The article examines how organizations leverage advanced IoT sensors, edge computing, and machine learning algorithms to address critical challenges in manufacturing downtime and operational efficiency. The article demonstrates how cloud-native AI solutions enable real-time data processing, predictive analytics, and automated decision-making in manufacturing environments through detailed analysis of implementation architectures, real-world case studies, and industry research. The article highlights the integration of various technological components, including data collection infrastructure, cloud processing capabilities, and analytics frameworks, while also addressing key considerations in data quality management, scalability, and security measures.
Keywords	Cloud-Native AI, Process Optimization, Real-Time Analytics, Serverless Computing, Enterprise Digital Transformation
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-05-16
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.44019

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