Virtualized Building Management Layer for Legacy BMS Integration
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Solution Overview
Problem
Existing building management systems (BMS) face inefficiencies due to poor capture of building usage requirements at startup, suboptimal configurations from changes in occupancy patterns and technical infrastructure, and challenges in integrating with cloud solutions, leading to redundant investments, manual migration issues, and costly integrations with legacy systems.
Innovation Solution
A hybrid cloud/on-premise model called GeoBMS, which includes a virtualization engine and APIs to integrate with on-premise BMS systems, enabling remote management, unified data representation, and multi-stakeholder access, while preserving existing investments and avoiding disruptive migrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pure play cloud BMS solutions are implemented, then scalability and remote access are improved, but existing on-premise BMS investments become redundant and integration with legacy systems becomes costly and time-consuming
Solution Approach 1:
The patent introduces a cloud-based intermediary layer that mediates between legacy on-premise BMS systems and modern cloud applications. This intermediary provides protocol translation and data normalization, allowing cloud solutions to access legacy systems without requiring complete system replacement or complex custom integrations for each legacy protocol.
Solution Approach 2:
The patent segments the BMS architecture into distinct layers: legacy device layer, protocol adaptation layer, data normalization layer, and application layer. This segmentation allows each layer to be independently optimized and replaced, enabling gradual migration from on-premise to cloud-based solutions while preserving existing investments.
2Adaptability or versatility
If on-premise BMS systems are manually migrated to cloud solutions, then cloud scalability is achieved, but migration activities become complicated and system downtime risks increase
Solution Approach 1:
The patent implements preliminary data normalization and standardization processes that prepare legacy BMS data for cloud consumption before actual migration occurs. This preliminary action includes creating unified data models and establishing cloud infrastructure in advance, enabling seamless cutover and reducing migration time and downtime risks.
Solution Approach 2:
The patent creates virtual copies of on-premise BMS functionality in the cloud environment, allowing parallel operation during migration. This copying approach enables validation of cloud-based systems before switching over, reducing migration risks and allowing rapid rollback if issues arise, thereby minimizing downtime.
3Reliability
If on-premise BMS systems are used, then existing investments are preserved, but energy optimization opportunities are missed due to poor capture of building usage requirements
Solution Approach 1:
The patent introduces dynamic configuration capabilities that allow cloud-based applications to continuously adapt to changing building usage patterns, occupancy levels, and environmental conditions. This dynamic approach enables real-time energy optimization while maintaining secure connections to existing on-premise BMS investments through standardized interfaces.
Solution Approach 2:
The patent implements comprehensive feedback loops that capture building usage requirements, occupancy data, and energy consumption patterns, then feed this information back to cloud-based optimization algorithms. These algorithms continuously refine energy management strategies, enabling significant energy optimization while preserving existing on-premise system investments.
Data Source
AI summary
Methods and apparatuses for virtualizing building management systems. An apparatus embodiment comprises a processor that receives a temperature adjustment command from a building application via a first application programming interface (API). The command specifies a target temperature for a designated space. The processor validates the access rights of the user for the command, translates the command into one or more device-specific control parameters, and communicates these parameters to an on-premise building management system via a second API. This enables execution of the temperature adjustment to achieve the desired temperature value for the building space.