Abstract: A heating, ventilation, and air conditioning (HVAC) control device configured to generate the machine learning model using the first set of weights and the second set of weights. The machine learning model is configured to output a probability that a user is present at the space based on an input that identifies a day of the week and a time of a day. The device is further configured to determine a probability that a user is present at the space for a predicted occupancy schedule using the machine learning model, to determine an occupancy status based on a determined probability that a user is present at the space, and to set a predicted occupancy status in the predicted occupancy schedule based on a determined occupancy status for each time entry. The device is further configured to output the predicted occupancy schedule.

Abstract: A heating, ventilation, and air conditioning (HVAC) control device is configured to record a plurality of actual occupancy statuses, to determine a plurality of corresponding predicted occupancy statuses, and to compare the plurality of predicted occupancy statuses to the plurality of actual occupancy statuses. The device is further configured to identify conflicting occupancy statuses based on the comparison. A conflicting occupancy status indicates a difference between an actual occupancy status and a corresponding predicted occupancy status. The device is further configured to identify timestamps corresponding with the conflicting occupancy statuses, to identify historical occupancy statuses corresponding with the identified timestamps, and to update the conflicting occupancy statuses in the predicted occupancy schedule with the historical occupancy statuses.

Abstract: A heating, ventilation, and air conditioning (HVAC) control device is configured to record a plurality of actual occupancy statuses, to determine a plurality of corresponding predicted occupancy statuses, and to compare the plurality of predicted occupancy statuses to the plurality of actual occupancy statuses. The device is further configured to identify conflicting occupancy statuses based on the comparison. A conflicting occupancy status indicates a difference between an actual occupancy status and a corresponding predicted occupancy status. The device is further configured to identify timestamps corresponding with the conflicting occupancy statuses, to identify historical occupancy statuses corresponding with the identified timestamps, and to update the conflicting occupancy statuses in the predicted occupancy schedule with the historical occupancy statuses.

Abstract: A heating, ventilation, and air conditioning (HVAC) control device is configured to record a plurality of actual occupancy statuses, to determine a plurality of corresponding predicted occupancy statuses, and to compare the plurality of predicted occupancy statuses to the plurality of actual occupancy statuses. The device is further configured to identify conflicting occupancy statuses based on the comparison. A conflicting occupancy status indicates a difference between an actual occupancy status and a corresponding predicted occupancy status. The device is further configured to identify timestamps corresponding with the conflicting occupancy statuses, to identify historical occupancy statuses corresponding with the identified timestamps, and to update the conflicting occupancy statuses in the predicted occupancy schedule with the historical occupancy statuses.

Abstract: A heating, ventilation, and air conditioning (HVAC) control device configured to receive a user input for controlling an HVAC system, to determine whether the user input indicates an energy saving occupancy setting, and to identify a first plurality of time entries that are associated with a confidence level for a predicted occupancy status that is less than a predetermined threshold value in the predicted occupancy schedule. The device is further configured to modify the predicted occupancy schedule by setting the first plurality of time entries to an away status when the user input indicates an aggressive energy saving occupancy setting. The device is further configured to modify the predicted occupancy schedule by setting the second plurality of time entries to a present status when the user input indicates a conservative energy saving occupancy setting. The device is further configured to output the modified predicted occupancy schedule.

Abstract: A heating, ventilation, and air conditioning (HVAC) control device configured to collect event data from the one or more devices and to populate time entries in an occupancy history log with the event data. The event data includes a timestamp indicating a time when an event occurred, a set point temperature value for the HVAC system, and an occupancy status indicating whether a space is occupied. The device is further configured to identify blank time entries in the occupancy history log and to populate the blank time entries by forward filling the occupancy history log using event data from another time entry in the occupancy history log. The device is further configured to output the populated occupancy history log.

Abstract: A heating, ventilation, and air conditioning (HVAC) control device is configured to record a plurality of actual occupancy statuses, to determine a plurality of corresponding predicted occupancy statuses, and to compare the plurality of predicted occupancy statuses to the plurality of actual occupancy statuses. The device is further configured to identify conflicting occupancy statuses based on the comparison. A conflicting occupancy status indicates a difference between an actual occupancy status and a corresponding predicted occupancy status. The device is further configured to identify timestamps corresponding with the conflicting occupancy statuses, to identify historical occupancy statuses corresponding with the identified timestamps, and to update the conflicting occupancy statuses in the predicted occupancy schedule with the historical occupancy statuses.

Abstract: A heating, ventilation, and air conditioning (HVAC) control device configured to generate the machine learning model using the first set of weights and the second set of weights. The machine learning model is configured to output a probability that a user is present at the space based on an input that identifies a day of the week and a time of a day. The device is further configured to determine a probability that a user is present at the space for a predicted occupancy schedule using the machine learning model, to determine an occupancy status based on a determined probability that a user is present at the space, and to set a predicted occupancy status in the predicted occupancy schedule based on a determined occupancy status for each time entry. The device is further configured to output the predicted occupancy schedule.

Abstract: A method of monitoring a HVAC system to detect erroneous sensor installation. The method includes determining whether a circulation fan has been operational for a first predetermined time interval. If the circulation fan has been operational for the first predetermined time interval, determining whether a cooling demand is present. If the cooling demand is present, determining whether the HVAC system has been conditioning air for the first predetermined time interval responsive to the cooling demand. If the HVAC system has been conditioning the air for the first predetermined time interval, determining whether a difference between an indoor air temperature value corresponding to an enclosed space and an air temperature value from a discharge air temperature (DAT) sensor is greater than a predetermined temperature value.

Abstract: A method of monitoring a HVAC system to detect erroneous sensor installation. The method includes determining whether a circulation fan has been operational for a first predetermined time interval. If the circulation fan has been operational for the first predetermined time interval, determining whether a cooling demand is present. If the cooling demand is present, determining whether the HVAC system has been conditioning air for the first predetermined time interval responsive to the cooling demand. If the HVAC system has been conditioning the air for the first predetermined time interval, determining whether a difference between an indoor air temperature value corresponding to an enclosed space and an air temperature value from a discharge air temperature (DAT) sensor is greater than a predetermined temperature value.

Abstract: A controller for an HVAC system comprises an interface, a memory, and a processor. The interface receives data related to user interactions with the system, and receives a temperature of the enclosed space. The memory stores an accumulated user discomfort value and discomfort score values, associated with user interactions. The processor determines a difference between the enclosed space temperature and a setpoint temperature. The processor determines whether the temperature difference exceeds a first threshold, and in response to determining that, determine whether a user has interacted with the system. In response to determining that the user has interacted with the system, the processor determines a current user discomfort value based on the discomfort score values, updates the accumulated user discomfort value, and determines whether the accumulated user discomfort value exceeds a second threshold.

Abstract: A method of monitoring a HVAC system to detect erroneous sensor installation. The method includes determining whether a circulation fan has been operational for a first predetermined time interval. If the circulation fan has been operational for the first predetermined time interval, determining whether a cooling demand is present. If the cooling demand is present, determining whether the HVAC system has been conditioning air for the first predetermined time interval responsive to the cooling demand. If the HVAC system has been conditioning the air for the first predetermined time interval, determining whether a difference between an indoor air temperature value corresponding to an enclosed space and an air temperature value from a discharge air temperature (DAT) sensor is greater than a predetermined temperature value.

Abstract: A controller for an HVAC system comprises an interface, a memory, and a processor. The interface receives data related to user interactions with the system, and receives a temperature of the enclosed space. The memory stores an accumulated user discomfort value and discomfort score values, associated with user interactions. The processor determines a difference between the enclosed space temperature and a setpoint temperature. The processor determines whether the temperature difference exceeds a first threshold, and in response to determining that, determine whether a user has interacted with the system. In response to determining that the user has interacted with the system, the processor determines a current user discomfort value based on the discomfort score values, updates the accumulated user discomfort value, and determines whether the accumulated user discomfort value exceeds a second threshold.