Building automation system and method using ceiling-mounted infrared sensors
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Solution Overview
Problem
Existing building automation systems are inefficient in anticipating and responding to occupant needs and space utilization, leading to occupant discomfort and wasteful energy use, as they rely on post-discomfort corrections rather than real-time adjustments.
Innovation Solution
A ceiling-mounted sensing unit that combines air temperature sensors and infrared sensors to estimate occupant-height temperature using machine-learning and Kalman filtering techniques, allowing for early detection of thermal load changes and proactive environmental adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional temperature sensors are used to monitor room temperature, then temperature can be measured, but the measurement does not reflect actual occupant-height temperature and responds too slowly to thermal load changes
Solution Approach 1:
The patent introduces an intermediary computational model that synthesizes data from multiple sensors (infrared sensors detecting radiant heat, air temperature sensors, occupancy detectors) to estimate occupant-height temperature. This intermediary layer translates indirect measurements into accurate occupant-centric temperature readings, resolving the contradiction between measurement availability and measurement accuracy.
Solution Approach 2:
The system performs preliminary detection of thermal load changes using infrared sensors that detect radiant heat from occupants before the air temperature actually changes. By detecting the presence and thermal signature of occupants in advance, the system can anticipate temperature changes and adjust environmental controls proactively, reducing the response time lag.
2Reliability
If environmental adjustments are made after occupant discomfort is detected, then the system responds to actual needs, but the correction occurs too late and energy is wasted
Solution Approach 1:
The system performs preliminary detection of thermal load changes using infrared sensors that detect radiant heat from occupants before the air temperature actually changes. By detecting the presence and thermal signature of occupants in advance, the system can anticipate temperature changes and adjust environmental controls proactively, reducing the response time lag.
Solution Approach 2:
The patent implements a feedback loop where the computational model continuously monitors occupancy status, infrared thermal signatures, and air temperature readings. This feedback mechanism allows the system to learn from patterns and predict when environmental adjustments will be needed, enabling proactive control decisions that prevent occupant discomfort before it occurs.
3Productivity
If building automation systems monitor space utilization, then resource deployment can be optimized, but the systems fail to accurately detect actual occupancy levels
Solution Approach 1:
The patent introduces an intermediary computational model that synthesizes data from multiple sensors (infrared sensors detecting radiant heat, air temperature sensors, occupancy detectors) to estimate occupant-height temperature. This intermediary layer translates indirect measurements into accurate occupant-centric temperature readings, resolving the contradiction between measurement availability and measurement accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables real-time environmental adjustments to enhance comfort and productivity by anticipating occupant needs, conserving energy, and reducing temperature fluctuations, thereby improving occupant comfort and energy efficiency.
Implementation Method 1
based on the readings of both air temperature sensors and at least one infrared (IR) temperature sensor, a method and a ceiling-mounted sensing unit estimate occupant-height temperature in a room
Implementation Method 2
The metal plate is a thermal conductor. The metal plate is maintained a temperature close to the temperature of the sensor body
Data Source
AI summary
A ceiling-mounted sensing unit includes (i) one or more air temperature sensors; (ii) an infrared sensor having a field of view oriented towards a floor of the room; and (iii) a microcontroller receiving readings from both the air temperature sensors and the infrared sensor, the microcontroller providing an estimated temperature at a predetermined distance above the floor of the room based on a model of the room. The model may be based on a double-exponential smoothing function obtained by matching a Kalman filter model. Alternately, the model may be itself a Kalman filter model or a machine learning trained linear model obtained using a linear regression technique, such as L2 regularization. The Kalman filter model uses a state vector that includes both the estimated temperature and a rate of change in the estimated change in temperature. The machine-trained model may be verified using a k-fold cross-validation technique.