Risk-Aware Predictive Analytics for Secure SAP-Enabled Digital Infrastructure in Pandemic Healthcare Waste Management
DOI:
https://doi.org/10.15662/IJEETR.2024.0606013Keywords:
Risk-Aware Analytics, Secure Digital Infrastructure, SAP Systems, Healthcare Waste Management, Cloud Computing, Predictive Modeling, Pandemic ResponseAbstract
Pandemic situations place unprecedented stress on healthcare systems, particularly in the management of medical waste, where failures can lead to severe environmental, operational, and public health risks. The rapid scaling of healthcare services during pandemics demands secure, resilient, and data-driven digital infrastructures capable of supporting complex business processes across distributed environments. This paper presents a risk-aware predictive analytics framework for secure SAP-enabled digital infrastructure designed to optimize healthcare waste management during pandemic conditions. The proposed architecture integrates cloud computing, artificial intelligence, and predictive analytics to monitor waste generation patterns, logistics workflows, and system performance in real time while proactively identifying operational, security, and compliance risks. By leveraging SAP-based business process integration and network-aware data analytics, the framework enables end-to-end visibility, automated risk mitigation, and resilient decision-making across decentralized healthcare facilities. Experimental evaluation and scenario-based analysis demonstrate that the proposed approach improves forecasting accuracy, enhances system security, and reduces process disruptions, thereby supporting safer, more efficient, and more reliable healthcare waste management operations in crisis situations.References
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