Selective carrying out of scheduled control operations by an intelligent controller
The current application is directed to intelligent controllers that use sensor output and electronically stored information to determine whether or not one or more types of entities are present within an area, volume, or environment monitored by the intelligent controllers. The intelligent controllers select operational modes and/or modify control schedules with respect to the presence and absence of the one or more entities. The intelligent controllers selectively carry out scheduled control operations during periods of time when one or more types of entities are determined not to be in a controlled environment.
1. An intelligent controller that controls an energy-consuming system that affects an environmental parameter within a controlled environment, the intelligent controller comprising:
a processor;
one or more sensors;
a memory that stores a control schedule comprising a plurality of scheduled setpoints and cumulative historical probability-of-presence data; and
instructions stored within the memory that, when executed by the processor, controls the intelligent controller to:
determine, from output of one or more of the one or more sensors, that no human being is present in the controlled environment for a predetermined time interval;
in response to determining that no human being is present in the controlled environment for the predetermined time interval, enter an away mode of operation where one or more environmental parameters are maintained at levels that are more energy-efficient than the scheduled setpoints; and
while operating in the away mode:
for each setpoint in the plurality of scheduled setpoints in the control schedule that occurs while operating in the away mode, determine, based at least in part on the historical probability-of-presence data, whether to carry out control operations to affect the environmental parameter using the energy-consuming system or whether to ignore the setpoint.
2. The intelligent controller of claim 1 wherein the intelligent controller determines, for each setpoint in the plurality of scheduled setpoints in the control schedule, whether to carry out the control operations to affect the environmental parameter using the energy-consuming system or whether to ignore the setpoint by:
for each control operation corresponding to a scheduled setpoint, evaluating the corresponding setpoint with respect to the cumulative historical probability-of-presence data to determine whether or not to carry out the control operation.
3. The intelligent controller of claim 2 wherein evaluating the corresponding setpoint with respect to the cumulative historical probability-of-presence data further comprises determining whether or not the cumulative historical probability-of-presence data indicates an increase in the probability of presence at the time of day of the setpoint corresponding to the control operation.
4. The intelligent controller of claim 3 wherein determining whether or not the cumulative historical probability-of-presence data indicates an increase in the probability of presence at the time of day of the setpoint corresponding to the control operation further comprises:
selecting a first time of day t1 prior to the time of day of the setpoint corresponding to the control operation, t;
selecting a second time of day t2 following the time of day of the setpoint corresponding to the control operation, t; and
when either the cumulative historical probability-of-presence at time of day t2 is greater than the cumulative historical probability-of-presence at time of day t or the cumulative historical probability-of-presence at time of day t is greater than the cumulative historical probability-of-presence at time of day t1, determining that the probability of presence at the time of day of the setpoint corresponding to the control operation is increasing and, otherwise, determining that the probability of presence at the time of day of the setpoint corresponding to the control operation is not increasing.
5. The intelligent controller of claim 1 wherein the intelligent controller determines, from output of one or more of the one or more sensors, that no human being is present in the controlled environment for the predetermined time interval at times within a range of times of day within which a determination of whether or not a human being is present can be reliably made.
6. The intelligent controller of claim 5 wherein the range of times of day within which a determination of whether or not a human being is present can be reliably made is determined from cumulative sensor data.
7. The intelligent controller of claim 5 wherein the range of times of day within which a determination of whether or not a human being is present can be reliably made is 8:00 AM until 8:00 PM.
8. The intelligent controller of claim 1 wherein the intelligent controller determines, for each setpoint in the plurality of scheduled setpoints in the control schedule, whether to carry out the control operations to affect the environmental parameter using the energy-consuming system or whether to ignore the setpoint by:
for each control operation corresponding to a scheduled setpoint,
evaluating the corresponding setpoint with respect to the cumulative historical probability-of-presence data to determine whether or not to carry out the control operation; and
when the evaluation of the corresponding setpoint indicates that the control operation is to be carried out, returning to maintenance of the one or more environmental parameters at energy-efficient levels for a variable threshold amount of time.
9. The intelligent controller of claim 8 wherein the variable threshold amount of time varies from a maximum variable threshold amount of time, immediately following a determination that no human being is present in the controlled environment, to 0, after an amount of time has elapsed that indicates a long-term absence of human beings in the controlled environment.
10. The intelligent controller of claim 9 wherein maximum variable threshold amount of time is 2 hours and the amount of elapsed time that indicates a long-term absence of human beings in the controlled environment is 2 days, with the variable threshold amount of time decreasing linearly over the period of 2 days.
11. The intelligent controller of claim 1 wherein control operations corresponding to scheduled setpoints include:
changing one or more environmental parameter settings at a time corresponding to a scheduled setpoint; and
changing one or more environmental parameter settings at a time prior to a time corresponding to a scheduled setpoint in order to carry out preconditioning.
12. The intelligent controller of claim 1 wherein the intelligent controller comprises a thermostat.
13. The intelligent controller of claim 12 wherein the one or more environmental parameters comprises a temperature.
14. The intelligent controller of claim 13 wherein the thermostat is in a heating mode and wherein the thermostat modifies the control schedule to maintain one or more environmental parameters at energy-efficient levels by setting a temperature setting to a specified away temperature below 70 degrees Fahrenheit and above 32 degrees Fahrenheit.
15. The intelligent controller of claim 13 wherein the thermostat is in a cooling mode and wherein the thermostat modifies the control schedule to maintain one or more environmental parameters at energy-efficient levels by setting a temperature setting to a specified away temperature above 65 degrees Fahrenheit and below 90 degrees Fahrenheit.
16. A method for controlling an energy-consuming system that affects an environmental parameter within a controlled environment by an intelligent controller that includes a processor, one or more sensors, a memory that stores a control schedule comprising a plurality of scheduled setpoints and stores cumulative historical probability-of-presence data, and instructions stored within the memory that, when executed by the processor, control the intelligent controller, the method comprising:
determining, from output of one or more of the one or more sensors, that no human being is present in the controlled environment for a predetermined time interval;
in response to determining that no human being is present in the controlled environment for the predetermined time interval, entering an away mode of operation where one or more environmental parameters are maintained at levels that are more energy-efficient than the scheduled setpoints; and
while operating in the away mode:
for each setpoint in the plurality of scheduled setpoints in the control schedule that occurs while operating in the away mode, determining, based at least in part on the historical probability-of-presence data, whether to carry out control operations to affect the environmental parameter using the energy-consuming system or whether to ignore the setpoint.
17. The method of claim 16 wherein determining, for each setpoint in the plurality of scheduled setpoints in the control schedule, whether to carry out the control operations to affect the environmental parameter using the energy-consuming system or whether to ignore the setpoint comprises:
for each control operation corresponding to a scheduled setpoint,
evaluating the corresponding setpoint with respect to the cumulative historical probability-of-presence data to determine whether or not to carry out the control operation.
18. The method of claim 17 wherein evaluating the corresponding setpoint with respect to the cumulative historical probability-of-presence data further comprises determining whether or not the cumulative historical probability-of-presence data indicates an increase in the probability of presence at the time of day of the setpoint corresponding to the control operation.
19. The method of claim 18 wherein determining whether or not the cumulative historical probability-of-presence data indicates an increase in the probability of presence at the time of day of the setpoint corresponding to the control operation further comprises:
selecting a first time of day t1 prior to the time of day of the setpoint corresponding to the control operation, t;
selecting a second time of day t2 following the time of day of the setpoint corresponding to the control operation, t; and
when either the cumulative historical probability-of-presence at time of day t2 is greater than the cumulative historical probability-of-presence at time of day t or the cumulative historical probability-of-presence at time of day t is greater than the cumulative historical probability-of-presence at time of day t1, determining that the probability of presence at the time of day of the setpoint corresponding to the control operation is increasing and, otherwise, determining that the probability of presence at the time of day of the setpoint corresponding to the control operation is not increasing.
20. The method of claim 16 wherein the intelligent controller comprises a thermostat, and the one or more environmental parameters comprises a temperature.