Cloud-Enabled Intelligent Ecosystem for BMS: SAP AI Integration with Secure Data Layers, Digital Forensics, and Energy-Aware DC-DC Conversion

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Published: 2023-09-13
DOI: https://doi.org/10.15662/IJRPETM.2023.0605003
Keywords:
Cloud Computing, SAP AI for Business, Building Management System (BMS), Secure Data Layers, Digital Forensics, DC-DC Converter, Machine Learning, Deep Learning, Energy Efficiency, Intelligent Ecosystem, Cybersecurity, Smart Infrastructure

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João Miguel Fernandes Silva
Senior Software Engineer, Portugal

Abstract

The convergence of artificial intelligence (AI), secure data architectures, and power-efficient systems is transforming the next generation of Building Management Systems (BMS). This paper proposes a cloud-enabled intelligent ecosystem that integrates SAP AI for Business, secure data layers, and digital forensics with an energy-aware DC-DC conversion framework. The objective is to develop an adaptive, transparent, and self-optimizing architecture for critical infrastructure such as healthcare and industrial facilities. The proposed BMS framework utilizes machine learning and deep learning algorithms within the SAP AI environment to enhance real-time analytics, automate control processes, and predict system anomalies. Secure data management layers, built on Oracle and SAP cloud infrastructures, provide end-to-end encryption, redundancy, and forensic traceability to safeguard operational and transactional data. The incorporation of digital forensics intelligence strengthens system resilience by enabling proactive threat detection, log auditing, and post-incident investigation capabilities. In parallel, the AI-regulated DC-DC converter design improves energy utilization and adaptive load balancing, supporting sustainable operation across distributed cloud nodes. Experimental evaluation indicates that the integrated model achieves a 28–35% improvement in energy efficiency, enhanced data integrity, and near-zero downtime in BMS performance. This research underscores the potential of AI-driven, cloud-enabled ecosystems in achieving secure, autonomous, and energy-efficient BMS modernization, paving the way for scalable deployments in smart healthcare and enterprise environments.

Article Details

Issue

Vol. 6 No. 5 (2023): International Journal of Research Publications in Engineering, Technology and Management

Section

Articles

How to Cite

Cloud-Enabled Intelligent Ecosystem for BMS: SAP AI Integration with Secure Data Layers, Digital Forensics, and Energy-Aware DC-DC Conversion. (2023). International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(5), 9321-9325. https://doi.org/10.15662/IJRPETM.2023.0605003

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