Building Automation Parameters Using Predecessor Building Data
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Solution Overview
Problem
The increasing number of sensors in building automation systems leads to higher production and maintenance costs without significantly improving energy efficiency, as existing methods rely solely on local data for closed-loop control.
Innovation Solution
A method and device that adapt building automation parameters by incorporating data from similar predecessor buildings, using static and weather data, to minimize energy consumption without the need for additional sensors, by applying scaling factors and optimizing parameters based on remote data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the number of sensors is increased to improve closed-loop control and minimize energy consumption, then energy efficiency is improved, but production and maintenance costs increase
Solution Approach 1:
The patent combines local sensor data from the building with remote weather data from predecessor buildings to create a hybrid data source. This merging allows the system to achieve better energy efficiency predictions without installing additional local sensors, thereby resolving the contradiction between improved energy efficiency and increased device complexity
Solution Approach 2:
The patent introduces an intermediary approach by using weather data from predecessor buildings as a mediator to supplement local sensor data. This intermediary data source provides additional information for energy efficiency optimization without requiring direct installation of more sensors at the target building, thus avoiding increased production and maintenance costs
2Loss of energy
If more sensor data is processed to improve closed-loop control, then energy efficiency is improved, but production and maintenance costs increase in an undesired way
Solution Approach 1:
The patent applies preliminary action by collecting and processing weather data from predecessor buildings in advance. This pre-collected remote data is then combined with local sensor data to improve energy efficiency predictions, eliminating the need to install and maintain additional sensors at the target building, thus avoiding increased production and maintenance costs
Data Source
AI summary
Provided is a method and a device for computer-assisted detection of building automation parameters of a building, wherein a first building automation having first building automation parameters is determined for the building, which first building automation is based on one or more classes of respectively local parameters. The classes of local parameters include at least one first class of static building data of the building, a second class of current weather data for the location of the building, and a third class of prior building automation parameters of the building. The first building automation parameters are adapted depending on a number of classes of distant parameters of at least one predecessor building, which is situated at a location that is different from the location of the building. The number of classes of distant parameters at the location or for the location of the respective predecessor building is determined.