Building Automation Self-Commissioning via Mobile Sensor Maps
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Solution Overview
Problem
Current building energy system commissioning parameters become sub-optimal over time due to changes in facility functionality, user behavior, and environmental conditions, leading to inefficient and labor-intensive re-commissioning processes that often lag behind performance compromises.
Innovation Solution
A system that utilizes sensor data from both fixed and mobile devices to collect and analyze environmental and user data, generating maps to detect changes and adjust commissioning parameters dynamically, thereby maintaining desired building performance through crowd-sourced data collection and real-time adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual re-commissioning is performed to update commissioning parameters, then system performance can be optimized, but labor cost and time consumption increase significantly
Solution Approach 1:
The system performs self-commissioning by automatically detecting environmental changes and adjusting commissioning parameters without human intervention. Sensors continuously monitor environmental quantities, and the processing unit automatically updates commissioning parameters when changes are detected, eliminating the need for manual re-commissioning and its associated time costs.
Solution Approach 2:
The system implements continuous feedback loops where sensor data about environmental changes is fed back to the processing unit, which then adjusts commissioning parameters in real-time. This closed-loop control ensures system performance is maintained automatically as conditions change, replacing periodic manual re-commissioning with continuous automated adjustment.
2Measurement precision
If fixed sensors are installed to collect environmental data, then measurement accuracy is improved, but installation cost and maintenance complexity increase
Solution Approach 1:
The system uses multi-functional mobile devices that citizens already possess (smartphones, tablets) to collect environmental data. These devices serve multiple purposes: they act as sensors for environmental quantities, navigation tools for location tracking, and communication devices for data transmission. This eliminates the need for dedicated fixed sensor installations while maintaining measurement capabilities through crowd-sourced data collection.
Solution Approach 2:
The system introduces a processing unit as an intermediary that aggregates, validates, and processes environmental data from multiple mobile device sources. This intermediary layer synthesizes crowd-sourced data to achieve the measurement accuracy that would otherwise require expensive fixed sensor installations, while significantly reducing installation and maintenance complexity.
Data Source
AI summary
A system and method for maintaining a system configuration to provide desired system performance is disclosed. The system comprises a processing unit receiving sensor data associated with environmental conditions within an area, generating a map of the area based on the received sensor data, determining a change in the map of the area and determining at least one system commissioning parameter associated with the determined change in the map to compensate for or correct the change in the map. In one aspect of the invention, the sensor data is provided through a plurality of mobile devices.