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AI-Based Intelligent Systems for Real-Time Data Processing and Analysis

Author(s) Prof. Dr. Por Lip Yee
Country Malaysia
Abstract The rapid growth of digital technologies has generated increasingly large volumes of data that require timely, accurate, and intelligent processing. Conventional data-processing approaches often face limitations when dealing with high-velocity, heterogeneous, and continuously changing data streams. Artificial intelligence (AI)-based intelligent systems provide an advanced approach by combining machine learning, automated pattern recognition, predictive analytics, and real-time computational capabilities.
This study examines the role of AI-based intelligent systems in real-time data processing and analysis and proposes an integrated framework for improving analytical efficiency, responsiveness, and decision-making. The study adopts a conceptual and descriptive research design based on secondary literature concerning artificial intelligence, real-time analytics, machine learning, stream processing, and intelligent decision-support systems. The proposed framework integrates data acquisition, preprocessing, real-time feature extraction, AI-based analytical modeling, continuous evaluation, and intelligent decision support.
The analysis indicates that AI-enabled systems can enhance the speed of data interpretation, identify complex patterns, support predictive decisions, and improve organizational responsiveness. However, challenges related to data quality, computational requirements, model transparency, cybersecurity, privacy, and continuous model adaptation remain significant. The study concludes that integrating AI with real-time data-processing architectures can provide a scalable foundation for advanced research and multidisciplinary intelligent applications.
Keywords Artificial Intelligence, Intelligent Systems, Real-Time Data Processing, Real-Time Analytics, Machine Learning, Predictive Analysis, Intelligent Decision-Making, Data-Driven Systems.
Field Engineering
Published In Volume 1, Issue 1, January-February 2019
Published On 2019-02-10
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