AI-Driven Software Ecosystem Engineering for Pediatric BMS Modernization: Digital Forensics, Risk Mitigation, Cloud-Enabled NLP, Image Denoising, and Cyber Data Vault Redundancy
DOI:
https://doi.org/10.15680/IJCTECE.2023.0604005Keywords:
AI-Driven Software Ecosystem, Pediatric BMS Modernization, Cloud Computing, Natural Language Processing (NLP);, Image Denoising, Cyber Data Vaults, Digital Forensics, Risk Mitigation, Healthcare IT Security, Cloud-Enabled Healthcare SystemsAbstract
The modernization of pediatric healthcare infrastructures increasingly requires resilient, intelligent, and secure IT ecosystems. This paper presents an AI-driven software ecosystem for pediatric Building Management System (BMS) modernization, integrating cloud-enabled natural language processing (NLP), image denoising, and cyber data vault redundancy. By embedding digital forensics and risk mitigation strategies, the framework enhances data integrity, security, and compliance across healthcare operations. NLP automates and analyzes clinical documentation, facilitating rapid decision support, while image denoising improves diagnostic imaging quality. Cyber data vaults ensure redundant, encrypted storage, safeguarding sensitive patient and operational data. The incorporation of forensic analytics enables proactive detection of anomalies, security breaches, and operational risks. Experimental simulations demonstrate measurable improvements in system resilience, threat detection accuracy, and clinical workflow efficiency, establishing a blueprint for secure, AI-enabled pediatric healthcare modernization.
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