Intelligent Data Analytics Platforms for Enhancing Resource Efficiency and Strategic Planning in Smart Infrastructures

Louies Meesy Lince

Authors

Louies Meesy Lince Research Scholar, Australia. Author

Keywords:

smart infrastructure, intelligent data analytics, machine learning, strategic planning, resource optimization, predictive analytics, digital transformation, operational efficiency, real-time monitoring, AI-driven decision making

Abstract

As smart infrastructures become increasingly complex, there is a growing need for intelligent systems capable of analyzing large-scale data streams to support strategic decision-making and optimize resource utilization. Intelligent Data Analytics Platforms (IDAPs), which combine artificial intelligence, machine learning, and advanced statistical techniques, offer a powerful solution for improving the performance and management of systems such as urban transportation networks, energy grids, and smart buildings. This paper examines the integration of IDAPs within smart infrastructure ecosystems, highlighting their role in enhancing operational efficiency and informing long-term planning. Through a structured review and the development of a conceptual framework, we outline the essential components of IDAPs, key implementation challenges, and the strategic benefits they offer for modern infrastructure management.

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