Smart building level control for improving compliance of temperature, pressure, and humidity
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Solution Overview
Problem
Existing building management systems struggle to efficiently monitor and maintain compliance with temperature, pressure, and humidity regulations, leading to potential operational disruptions and financial penalties, particularly in critical environments like hospitals.
Innovation Solution
A building management system (BMS) that utilizes predictive models to monitor and control HVAC parameters, integrating sensor arrays and calibration units to predict and maintain compliance with regulatory standards by adjusting HVAC equipment operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional monitoring systems are used to check TPH compliance, then compliance can be detected, but the system cannot predict future compliance issues and requires frequent manual inspections
Solution Approach 1:
The system performs preliminary actions by continuously collecting and analyzing TPH data to predict future compliance issues before they occur. The predictive model forecasts potential non-compliance scenarios, allowing the system to take preventive measures ahead of time, eliminating the need for frequent reactive inspections.
Solution Approach 2:
The system implements continuous feedback loops where TPH sensor data is constantly monitored, analyzed by machine learning models, and used to adjust HVAC controls in real-time. This closed-loop feedback mechanism ensures compliance is maintained automatically without manual intervention.
2Reliability
If manual compliance checking is performed, then compliance status can be identified, but operational disruptions occur when non-compliance is detected
Solution Approach 1:
The system performs self-service by automatically detecting compliance status, predicting potential issues, and adjusting HVAC equipment without human intervention. The autonomous predictive control system maintains compliance continuously, eliminating operational disruptions associated with manual checking and reactive corrections.
Solution Approach 2:
By predicting compliance issues before they manifest, the system takes preliminary corrective actions automatically, preventing operational disruptions before they occur. This proactive approach ensures continuous compliance without stopping or disrupting hospital operations.
3Reliability
If reactive compliance correction is implemented, then non-compliance issues can be fixed, but the process is expensive and time-consuming
Solution Approach 1:
The system performs preliminary compliance corrections by predicting future non-compliance scenarios and automatically adjusting HVAC parameters in advance. This prevents the need for time-consuming reactive corrections, as compliance issues are addressed before they occur.
Solution Approach 2:
Continuous real-time feedback from predictive models enables immediate automatic corrections to maintain compliance. The system detects trends and adjusts controls proactively, eliminating the delayed corrective actions that characterize reactive systems.
4Reliability
If frequent inspections are conducted to ensure compliance, then compliance can be maintained, but hospital operations are disrupted
Solution Approach 1:
The system maintains compliance through self-service automated monitoring and control, eliminating the need for frequent manual inspections. The predictive model continuously assesses compliance status and automatically adjusts HVAC systems, maintaining reliability without disrupting hospital operations.
Solution Approach 2:
The system ensures continuous compliance monitoring and adjustment without interruption to hospital operations. The predictive control system operates continuously in the background, maintaining TPH parameters within compliance ranges while allowing normal hospital activities to proceed uninterrupted.
Data Source
AI summary
A building management system for monitoring and controlling HVAC parameters in a building includes one or more processing circuits configured to initialize a predictive model for predicting temperature, pressure, and humidity within a target area and an adjacent area of the building, receive target area data from a target area sensor array configured to measure temperature, pressure, and humidity of the target area, receive adjacent area data from an adjacent area sensor array configured to measure temperature, pressure, and humidity of the adjacent area, execute the predictive model based on the target area data and the adjacent area data to generate a prediction of future temperature, pressure, and humidity within the target area, and control operation of HVAC equipment to maintain the temperature, pressure, and humidity of the target area within a compliance standard.