HVAC Temperature Voting Using Occupant Preference Aggregation
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Solution Overview
Problem
Traditional HVAC systems in commercial buildings often require frequent adjustments to meet varying occupant preferences, leading to inefficient temperature control and potential dissatisfaction, as they react to individual complaints rather than collective preferences.
Innovation Solution
A temperature control voting system that aggregates votes from occupants within an HVAC zone, using smartphone applications, near-field communication devices, and biomedical devices to determine an optimal set-point temperature, with vote weighting based on occupant status and location, allowing for automatic adjustment of the HVAC system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the building engineer manually adjusts the HVAC system in response to individual complaints, then the responding speed to occupant needs is improved, but the temperature control accuracy deteriorates because it cannot reflect collective preferences
Solution Approach 1:
The system implements automated feedback collection through smartphone applications and sensors that continuously gather temperature preferences from multiple occupants. This feedback mechanism replaces manual complaint processing with systematic data collection, enabling the HVAC system to respond to aggregate occupancy preferences rather than individual complaints, thus improving both response speed and temperature control accuracy.
Solution Approach 2:
The patent replaces the mechanical system of manual engineer intervention with an automated electronic system comprising smartphone applications, wireless communication modules, and HVAC control integration. This substitution eliminates the need for physical visits by building engineers while capturing real-time temperature preferences from multiple occupants simultaneously, resolving the contradiction between response speed and accuracy.
2Adaptability or versatility
If the building engineer constantly adjusts the air temperature throughout the day, then the adaptability to varying occupant preferences is improved, but the loss of time and efficiency deteriorates
Solution Approach 1:
The system enables self-service temperature control by allowing occupants to submit their temperature preferences through smartphone applications. The HVAC system automatically processes these inputs and adjusts settings without requiring engineer intervention. This self-service mechanism maintains high adaptability to varying preferences while eliminating the time loss associated with constant manual adjustments.
Solution Approach 2:
The system performs preliminary action by proactively collecting temperature preferences from occupants before conflicts arise. Through continuous monitoring and aggregation of preferences, the system anticipates temperature adjustment needs and makes adjustments in advance, reducing the need for reactive engineer interventions and minimizing time loss.
3Adaptability or versatility
If the HVAC system serves multiple occupants with different temperature preferences, then the versatility of temperature control is improved, but the difficulty of detecting and measuring collective preference increases
Solution Approach 1:
The smartphone application serves multiple functions: it collects temperature preferences, identifies occupant locations within the building, aggregates data from multiple users, and communicates with the HVAC system. This multi-functional approach simplifies the detection and measurement of collective preferences by consolidating multiple tasks into a single universal platform.
Solution Approach 2:
The system introduces an intermediary layer consisting of the smartphone application and central processing server that mediates between individual occupant preferences and the HVAC control system. This intermediary aggregates and processes raw preference data from multiple occupants, transforming it into actionable control signals, thereby reducing the difficulty of detecting and measuring collective preferences.
Data Source
AI summary
A temperature voting system which receives votes indicating the temperature preferences of a plurality of occupants within a given HVAC zone, and adjusts a set-point temperature of a corresponding HVAC system accordingly. The votes may be received via a mobile device, an employee workstation, or from one or more biomedical devices. Each occupant may manually enter and submit a vote for their preferred set-point temperature, or a software application may be configured to automatically cast a vote for the corresponding occupant according to user-configurable preferences or current metabolic state. The received votes may be weighted according to a status of the voter, and aggregated to determine an appropriate set-point temperature. In some embodiments, near-field communication devices, GPS location technology, or other technology may be used to automatically detect the presence of an occupant within a HVAC zone and cast the occupant's vote for a corresponding HVAC zone.