Intelligent AI-Cloud Architecture for Building Management Systems Using KNN and SAP-Based Data Intelligence
DOI:
https://doi.org/10.15662/IJARCST.2025.0806006Keywords:
AI-Cloud Architecture, Building Management Systems (BMS), K-Nearest Neighbor (KNN), SAP Data Intelligence, Predictive Analytics, Smart Infrastructure, Energy Optimization, Real-Time MonitoringAbstract
This paper presents an Intelligent AI-Cloud Architecture for Building Management Systems (BMS) that leverages K-Nearest Neighbor (KNN) algorithms and SAP-based data intelligence to enable predictive, adaptive, and efficient facility management. The proposed architecture integrates Artificial Intelligence (AI) and Cloud Computing to support real-time data acquisition, analysis, and decision-making across distributed building infrastructures. KNN-based analytics enhance fault detection, energy optimization, and occupancy pattern recognition, while SAP integration facilitates data visualization, workflow automation, and enterprise-level transparency. The framework ensures interoperability between IoT-enabled devices, cloud services, and enterprise systems, allowing scalable and secure management of environmental, energy, and operational parameters. By combining machine learning precision with SAP-driven data governance, the architecture enables proactive maintenance, sustainability, and resource efficiency, forming a foundation for next-generation smart and self-adaptive BMS ecosystems.
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