Automated cloud hosted BMS archive and difference engine
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing building management systems lack efficient methods for determining updates and managing changes in configuration data, leading to inefficiencies and potential increases in energy costs.
Innovation Solution
A method utilizing a cloud-based difference engine to compare current and previous configuration data sets within a building management system, identifying deltas such as equipment changes and energy cost impacts, and providing updates or restoration instructions through an interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of stationary object
If configuration data is stored locally in the BMS, then access speed is fast, but storage capacity and data security are limited
Solution Approach 1:
The patent introduces a cloud server as an intermediary between the BMS and configuration storage. The cloud server receives configuration data from the BMS via an on-premise server, providing secure off-site storage while maintaining data accessibility. This mediator resolves the contradiction by enabling both large storage capacity and enhanced data security through remote hosting.
Solution Approach 2:
The patent transitions configuration data storage from a local single-dimension approach to a distributed cloud-based multi-dimensional architecture. By moving data to the cloud, the system gains additional dimensions in terms of storage scalability, geographic distribution, and access flexibility, thereby increasing both storage capacity and security without compromising local operational speed.
2Measurement precision
If all configuration data is monitored and compared, then change detection is comprehensive, but processing time and computational resources increase
Solution Approach 1:
The patent extracts only the essential configuration data elements that are subject to change and monitors those specifically, rather than processing entire configuration data sets. The difference engine compares specific configuration parameters between time periods, identifying only relevant changes. This extraction approach maintains comprehensive change detection accuracy while significantly reducing processing time and computational overhead.
Solution Approach 2:
The patent applies partial action by performing selective comparison of configuration data rather than complete data set analysis. The difference engine focuses on comparing specific configuration elements that are likely to change, such as equipment additions or parameter modifications, while ignoring stable elements. This partial monitoring approach achieves sufficient change detection precision with reduced processing requirements.
3Adaptability or versatility
If configuration changes are implemented immediately, then system adaptability is high, but system stability and error risk increase
Solution Approach 1:
The patent implements preliminary action by performing difference analysis and change validation before actual configuration changes are applied to the BMS. The system identifies configuration deltas, presents them for review, and only implements changes after verification. This preliminary validation step enables the system to adapt to necessary changes while maintaining stability by preventing erroneous or premature modifications.
Solution Approach 2:
The patent incorporates feedback mechanisms where the difference engine continuously monitors configuration changes and provides information about detected deltas. This feedback loop allows operators to review proposed changes, understand their impact, and approve or reject modifications. The feedback process balances adaptability by enabling necessary changes while maintaining reliability through controlled implementation and verification.
Data Source
AI summary
A method for determining updates in a building management system (BMS) is shown. The method includes receiving, via an on premise server, configuration data associated with at least part of the BMS. The method includes storing the configuration data within a cloud server communicably coupled with the on premise server. The method includes determining, via a difference engine within the cloud server, information comprising a delta between the configuration data and one or more previous sets of configuration data stored within the cloud server. The method includes providing, to the on premise server, the information to an interface.