Methodology of occupant comfort management in buildings using occupant comfort models and user interfaces thereof
Disclosed is a system and method for managing the comfort of building occupants. The system utilizes a model-based approach for targeting occupant comfort levels. The system allows for voting input from building occupants regarding their respective comfort. Additionally, the system provides a user interface to gather occupant input and use said input as a parameter in a comfort model.
1. An environmental control system, comprising:
a plurality of occupant proxies, one or more non-human asset proxies, a comfort model, a meta-proxy, and an output function, wherein:
the comfort model comprises a mathematical equation of human comfort, the mathematical equation comprising or derived from predicted mean vote (“PMV”) and predicted percentage of dissatisfied (“PPD”);
the plurality of occupant proxies each comprise a comfort state of an individual occupant;
the one or more non-human asset proxies each comprise a comfort model for a non-human asset in or proximate to a building, the comfort model for the non-human asset comprising a mathematical equation of building asset comfort for the building, the mathematical equation of building asset comfort comprising one or more of an equipment environmental operation model, a metallic rust model, a building material moisture capacity model, a building material mold potential model, an animal comfort model, a plant health model, and a water freeze model;
the comfort state comprises a function of the comfort model;
the meta-proxy comprises a combined function of the plurality of occupant proxies and the one or more non-human asset proxies;
the output function comprises a building system control path for the building as a function of the meta-proxy; and
the output function receives the meta-proxy as an input and provides the building system control path as a path-based control output to control a building system for the building based on a combination of both the plurality of occupant proxies and the one or more non-human asset proxies.
2. The environmental control system of claim 1 , wherein said comfort model comprises a mathematical equation of human comfort.
3. The environmental control system of claim 2 , wherein said equation comprises one or more of the variables: air temperature, radiant temperature, air velocity, humidity, metabolic rate, skin temperature, skin wettedness, total evaporative heat loss from skin, skin surface area, sweat rate, body mass, skin mass, body mass-index, gender, age, occupancy, ethnicity, locality, and/or clothing insulation value.
4. The environmental control system of claim 2 , wherein said equation is comprised or is a derivative of one or more of the following: Fanger Model, KSU Two-Node Model, ASHRAE 55, Pierce Two-Node Model, Standard Effective Temperature Model, Adaptive Comfort Model.
5. The environmental control system of claim 1 , wherein said proxies comprise the comfort states of said occupants.
6. The environmental control system of claim 1 , wherein said 7function may be comprised of, but not limited to, one or more of the following techniques: averaging methods, such as arithmetic mean, geometric mean, harmonic mean, trimean, median, mode, mid-range, quadratic mean (RMS), cubic mean, generalized mean, weighted mean; machine learning and statistical techniques, such as linear regression, logistic regression, polynomial regression, k-means clustering, k-nearest neighbors, decision trees, perceptron, multi-layer perceptron (neural network), kernel methods, support vector machines, ensemble methods, boosting, bagging, naïve Bayes, expectation maximization, Gaussian mixture models, Gaussian processes, principal component analysis, singular value decomposition, reinforcement learning, Voronoi decomposition; and social theory voting techniques and concepts, such as social welfare functions, social choice functions, single transferrable vote, Bucklin's rule, social decision schemes, collective utility functions, and Condorcet method and extensions such as Copeland's rule, maximin, Dodgson's rule, Young's rule, and ranked pairs.
7. The environmental control system of claim 1 , wherein said output function may be comprised of, but not limited to, one or more system set-point adjustments, time series control paths, or predictive control paths.
8. The environmental control system of claim 1 , wherein said output function may be comprised of, but not limited to, the control of air temperature, radiant temperature, humidity, air flow, lighting, and air flow noise.
9. An electronic device or network of electronic devices comprising:
a motion sensor component;
at least one memory; and
one or more processors operatively coupled to the motion sensor component and one or more processors operatively coupled to the at least one memory, where the processors are configured to execute program code stored in the at least one memory to:
receive motion measurements obtained with the motion sensor component;
analyze the motion measurements to identify a degree of metabolic energy generated at least in part by the measured motion;
compute a comfort of a mobile user via a human comfort model, the human comfort model comprising a mathematical equation of human comfort, the mathematical equation comprising or derived from predicted mean vote (“PMV”) and predicted percentage of dissatisfied (“PPD”);
compute, using an output function that receives a meta-proxy as an input, the meta-proxy comprising an occupant proxy for the mobile user based on the computed comfort and a non-human asset proxy for a non-human asset, a control offset between a combination of the comfort of the mobile user and a comfort for the non-human asset, and current environmental conditions, thus generating a control path as a path-based control output to control an environmental control system, the non-human asset proxy comprising a comfort model for a non-human asset in or proximate to a building, the comfort model for the non-human asset comprising a mathematical equation of building asset comfort, the mathematical equation of building asset comfort comprising one or more of an equipment environmental operation model, a metallic rust model, a building material moisture capacity model, a building material mold potential model, an animal comfort model, a plant health model, and a water freeze model; and
transmit the control path to the environmental control system.
10. The electronic device of claim 9 , wherein the motion sensor comprises a sensor or sensors that measure user movement, motion, heart rate, blood oxygen levels, accelerometers, gyroscopes, angular velocity, direction, GPS, and/or other activity sensors.
11. The electronic device of claim 9 , wherein the electronic device is comprised of a mobile, wearable, handheld, and/or other person-attached electronic device.
12. The electronic device of claim 9 wherein the motion sensor is part of one or more devices, and some or all of the computation of claim 9 is performed on one or more external networked electronic devices.
13. The electronic device of claim 9 wherein the metabolic rate is computed periodically, and internally accumulated, such that the human comfort model comprises an internal heat capacity and a heat balance, the internal heat capacity and the heat balance representing a temporal comfort state of the occupant.
14. A system for a user interface representation of human comfort preferences in a human comfort model proxy driven environmental control system, the system comprising:
a computing device with a display;
an application interface;
objects in a graphical user interface, of the type in which representations of objects stored in a memory are displayed to a user on the display, wherein the objects comprise abstractions of comfort model parameters representing one or more human factors in the human comfort model proxy and one or more non-human factors in a non-human asset proxy for a non-human asset in or proximate to a building associated with the environmental control system; and
whereby:
the comfort model parameters, in conjunction with environmental parameters, are used to calculate the human comfort model proxy, the human comfort model proxy comprising a mathematical equation of human comfort, the mathematical equation comprising or derived from predicted mean vote (“PMV”) and predicted percentage of dissatisfied (“PPD”); and
the human comfort model proxy and the non-human asset proxy are used as input into an output function to compute a control path as a path-based control output of the output function to control the environmental control system, the non-human asset proxy comprising a comfort model for the non-human asset in or proximate to the building, the comfort model for the non-human asset comprising a mathematical equation of building asset comfort, the mathematical equation of building asset comfort comprising one or more of an equipment environmental operation model, a metallic rust model, a building material moisture capacity model, a building material mold potential model, an animal comfort model, a plant health model, and a water freeze model.
15. The system of claim 14 , wherein the abstractions of comfort model parameters comprise an abstraction of one or more of, but not limited to, metabolic rate, body mass, body mass-index, gender, age, occupancy, ethnicity, locality, and/or clothing insulation value.
16. The system of claim 15 , wherein the user interface comprises a comfort input control for an occupant.
17. The system of claim 16 , wherein the objects comprise an abstraction of, at least in part, a clothing insulation parameter of the comfort model parameters.
18. The system of claim 16 , wherein the objects in the graphical user interface comprise an abstraction of a human comfort range, that computes an acceptable range within a standardized comfort scale that is computed by the human comfort model proxy.
19. The system of claim 16 , wherein the abstractions of comfort model parameters comprise user inputs in a priori stored profile of the occupant.