HVAC Alerting Gateway With Adaptive Polling and Capacity Diagnostics
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Solution Overview
Problem
Small to medium-sized HVAC contractors face inefficiencies in managing and interpreting large volumes of data for building comfort and equipment health, leading to burdensome workflows and a need for a simplified alerting system that provides timely and valuable notifications.
Innovation Solution
A notification system that incorporates sensors to detect equipment events, logs alerts when thresholds are crossed, and allows for customizable alert priorities and delivery methods, along with a gateway that dynamically adjusts poll rates based on application needs, and implements analytics to detect HVAC capacity loss and comfort control issues using relative degree days and proportional error calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional alerting systems are used to monitor equipment events, then comprehensive monitoring coverage is achieved, but data overload and workflow complexity increase for contractors
Solution Approach 1:
The patent segments alert information by priority levels (high, medium, low) and categorizes events into distinct types (equipment failures, comfort issues, efficiency problems). This segmentation allows contractors to focus on critical issues first while reducing the perceived complexity of managing comprehensive monitoring data.
Solution Approach 2:
The system extracts and highlights only the most relevant alert information based on priority levels and contractor preferences. By taking out essential alert details from the comprehensive data set and presenting them in a simplified format, the system maintains reliable monitoring coverage while reducing workflow complexity.
2Measurement precision
If detailed analytics are implemented to detect HVAC capacity loss and comfort issues, then diagnostic accuracy is improved, but computational resources and system complexity increase
Solution Approach 1:
The system performs preliminary calculations of key metrics such as degree days, proportional errors, and capacity ratios directly at the controller level before transmitting data to the cloud. This preliminary action reduces the computational burden on centralized systems while maintaining high diagnostic accuracy for detecting HVAC capacity loss and comfort issues.
Solution Approach 2:
The patent introduces intermediate processing layers that aggregate and pre-analyze data locally before sending it to the cloud platform. These intermediaries perform initial filtering and calculation of diagnostic metrics, reducing the complexity of the overall system while preserving measurement precision through multi-stage analysis.
3Reliability
If continuous monitoring of multiple parameters is performed, then early detection of equipment issues is achieved, but energy consumption and data processing loads increase
Solution Approach 1:
The system implements periodic monitoring with variable intervals based on equipment status and priority levels. Critical parameters are monitored continuously, while non-critical parameters are checked at lower frequencies. This periodic action enables early detection of equipment issues while reducing overall data processing energy consumption.
Solution Approach 2:
The patent dynamically adjusts monitoring parameters and thresholds based on equipment operating conditions, seasonality, and historical data. By changing parameters adaptively rather than using fixed continuous monitoring, the system achieves early detection capability while optimizing energy consumption for data processing.
Data Source
AI summary
A program for light commercial building system (LCBS) solutions. Solutions and other systems may incorporate lightweight alerting service, auto-adjustment of gateway poll rates based on the needs of various consuming applications, detecting loss of space comfort control in a heating, ventilation and air conditioning (HVAC) system, HVAC capacity loss alerting using relative degree days and accumulated stage run time with operational equivalency checks, and HVAC alerting for loss of heat or cool capacity using delta temperature and dependent system properties. Also, incorporated may be triggering s subset of analytics by automatically inferring HVAC equipment details from controller configuration details, ensuring reliability of analytics by retaining logical continuity of HVAC equipment operational data even when controllers and other parts of the system are replaced, and an LCBS gateway with workflow and mechanisms to associate to a contractor account.