Autonomous Infrastructure Optimization and Predictive Analytics for Healthcare Finance and Public Service Ecosystems
DOI:
https://doi.org/10.21590/ijtmh.11.04.16Keywords:
Predictive Analytics, Autonomous Infrastructure, Artificial Intelligence, Healthcare Systems, Financial Technology, Public Service Platforms, Machine Learning, Infrastructure Optimization, Cloud Computing, Big Data Analytics, Cybersecurity, Smart Governance, Intelligent Automation, Data Privacy, Digital Transformation.Abstract
Predictive analytics and autonomous infrastructure optimization are transforming modern digital ecosystems across healthcare, finance, and public service sectors. Organizations increasingly depend on data-driven technologies to improve operational efficiency, resource allocation, decision-making, and service delivery. Predictive analytics uses machine learning, statistical modeling, and artificial intelligence techniques to analyze historical and real-time data for forecasting future outcomes and identifying hidden patterns. Autonomous infrastructure optimization further enhances system performance by enabling self-managing, adaptive, and intelligent infrastructures capable of automated monitoring, scaling, maintenance, and threat detection. In healthcare, predictive systems improve patient diagnosis, disease forecasting, and hospital resource management. In finance, predictive analytics supports fraud detection, investment forecasting, credit risk analysis, and automated trading systems. Public service platforms utilize intelligent optimization to improve governance, transportation management, emergency response, and citizen-centric digital services. Despite these advantages, challenges related to cybersecurity, data privacy, algorithmic bias, explainability, and regulatory compliance continue to affect implementation. This study explores the role of predictive analytics and autonomous optimization technologies in improving efficiency, scalability, resilience, and sustainability across critical sectors. The research also evaluates existing methodologies, governance mechanisms, and technological frameworks that support secure and intelligent infrastructure management in modern enterprise and public service environments.
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