Crowd-Sourced HVAC Control Using Geo-Located Occupant Comfort Reports
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Solution Overview
Problem
Building occupants often experience discomfort due to temperature and air quality issues, which can indicate inefficient HVAC design or operation, leading to discomfort and potential health problems, and there is a need for an efficient system to capture and address comfort and maintenance information effectively.
Innovation Solution
A computer-implemented system in a client-server environment that enables crowd-sourced report generation, aggregation, and response, allowing users to generate thermal and maintenance reports, which are geo-located, aggregated, and used to inform building management decisions, including automatic adjustments to HVAC systems based on occupant feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional HVAC control systems are used, then system operation is maintained, but occupant comfort cannot be effectively monitored or improved
Solution Approach 1:
The system implements a feedback mechanism where occupants can submit comfort reports through a mobile application, and this feedback is aggregated and analyzed to automatically adjust HVAC system operations. The feedback loop closes when system adjustments are made based on the collected data, continuously improving occupant comfort.
Solution Approach 2:
The system enables occupants to self-report comfort issues without requiring manual intervention from facility management. The automated aggregation and analysis of reports, combined with automatic system adjustments, allows the building management system to serve itself in responding to occupant needs.
2Productivity
If manual comfort reporting is used, then some feedback is captured, but the process is inefficient and does not scale well
Solution Approach 1:
The system replaces manual comfort reporting mechanisms with an automated electronic system. Occupants use a mobile application to submit reports, which are then automatically aggregated, analyzed, and processed by the system, eliminating the need for manual data collection and processing methods.
Solution Approach 2:
The system introduces a digital intermediary layer between occupants and the HVAC control system. The mobile application and automated aggregation system serve as intermediaries that efficiently capture, transmit, and process comfort feedback, enabling rapid response without direct manual intervention.
3Use of energy by moving object
If HVAC systems operate without automated adjustments, then system stability is maintained, but energy efficiency cannot be optimized
Solution Approach 1:
The system introduces dynamic control capabilities to the HVAC system, allowing it to automatically adjust operations based on real-time comfort feedback and environmental conditions. This enables the system to adapt its behavior dynamically rather than operating on fixed schedules or manual controls.
Solution Approach 2:
The system automatically modifies HVAC operational parameters such as temperature setpoints, airflow rates, and equipment operation schedules based on aggregated comfort reports and environmental sensor data, optimizing energy consumption while maintaining occupant comfort.
4Measurement precision
If detailed comfort monitoring is implemented, then comfort issues can be identified, but system complexity increases
Solution Approach 1:
The system segments the comfort monitoring function into distinct components: a mobile application for data entry, an automated aggregation system for data collection, an analysis module for interpreting feedback, and a control module for system adjustments. This segmentation allows each component to be independently optimized and managed.
Data Source
AI summary
A system and method for crowd-sourced environmental system control and building maintenance includes a server for providing selective access to building occupants and managers. Users are permitted to generate building reports in the form of (i) thermal reports using a thermal report module, and/or (ii) maintenance reports using a maintenance report module. The reports are each geo-located to locations within the building, and are then captured, stored, and aggregated at the server. The aggregated reports are sorted according to their geo-locations and comfort rules are used to (i) permit a manager at a client computer to access the server to respond, and/or (ii) automatically respond and assign a response status to particular reports. An inspection checklist interface is generated and populated to display a list of preventative maintenance tasks, each of the tasks being user-selectable to designate completion, with the updated status of the reports being stored at the server.