AI-Driven 3D Reconstruction from 2D Scans: Risk-Aware Cloud Architectures with Azure Data Lake and SAP Integration
DOI:
https://doi.org/10.15662/IJRAI.2025.0804009Keywords:
AI-driven 3D reconstruction, 2D scan processing, Cloud computing architecture, Azure Data Lake, SAP integration, Risk-aware governance, Data security and compliance, Machine learning pipelines, Enterprise data management, Secure cloud workflowsAbstract
The rapid advancement of artificial intelligence (AI) and cloud computing has enabled scalable, efficient, and accurate 3D reconstruction from 2D scan data. However, the integration of AI-driven workflows with enterprise systems such as SAP, coupled with cloud data storage solutions like Azure Data Lake, introduces significant security, compliance, and risk management challenges. This paper proposes a risk-aware cloud architecture for AI-driven 3D reconstruction pipelines, focusing on secure data ingestion, storage, and processing while ensuring compliance with enterprise governance policies. The architecture leverages machine learning algorithms to reconstruct high-fidelity 3D models from 2D scans, seamlessly integrating with SAP modules for enterprise-level analytics and decision-making. Key components include role-based access control, data encryption, audit logging, and anomaly detection, providing a holistic approach to risk mitigation in cloud-based AI workflows. Experimental evaluation demonstrates the architecture’s effectiveness in maintaining data security, minimizing computational overhead, and achieving accurate 3D reconstruction across diverse datasets. The proposed framework offers a blueprint for organizations seeking to implement AI-driven 3D reconstruction in secure, compliant, and scalable cloud environments.
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