Abstract:
A method includes receiving an estimated time of arrival (ETA) relating to an arrival to an environment, an arrival of an event, arrival of an activity, or a combination thereof; and controlling, configuring, or controlling and configuring a smart device based upon the ETA.
Abstract:
Systems and methods for controlling a climate control system of a smart-home environment that includes a plurality of smart devices are provided. One method includes detecting, with a hazard detector of the smart devices, a level of carbon monoxide (CO) at the hazard detector that exceeds a threshold CO level at a location of the hazard detector, determining, by one of the smart devices, that the climate control system includes a combustion based heat source, and in response to the detecting and the determination, transmitting, by a system controller of the climate control system, a first signal to turn off at least one aspect of the climate control system.
Abstract:
In an embodiment, an electronic device may include a processor that may iteratively simulate candidate control trajectories using upper confidence bound for trees (UCT) to control an environmental control system (e.g., an HVAC system). Each candidate control trajectory may be simulated by selecting a control action at each of a plurality of time steps over a period of time that has the highest upper bound on possible performance using values from previous simulations and predicting a temperature for a next time step of the plurality of time steps that results from applying the selected control action using a thermal model. The processor may determine a value of each candidate control trajectory using a cost function, update the value of each control action selected in each candidate control trajectory, and select a candidate control trajectory with the highest value using UCT to apply to control the environmental control system.
Abstract:
In an embodiment, an electronic device may include a processor that may iteratively simulate candidate control trajectories using upper confidence bound for trees (UCT) to control an environmental control system (e.g., an HVAC system). Each candidate control trajectory may be simulated by selecting a control action at each of a plurality of time steps over a period of time that has the highest upper bound on possible performance using values from previous simulations and predicting a temperature for a next time step of the plurality of time steps that results from applying the selected control action using a thermal model. The processor may determine a value of each candidate control trajectory using a cost function, update the value of each control action selected in each candidate control trajectory, and select a candidate control trajectory with the highest value using UCT to apply to control the environmental control system.
Abstract:
Systems and methods for controlling a climate control system of a smart-home environment that includes a plurality of smart devices are provided. One method includes detecting, with a hazard detector of the smart devices, a level of carbon monoxide (CO) at the hazard detector that exceeds a threshold CO level at a location of the hazard detector, determining, by one of the smart devices, that the climate control system includes a combustion based heat source, and in response to the detecting and the determination, transmitting, by a system controller of the climate control system, a first signal to turn off at least one aspect of the climate control system.
Abstract:
In an embodiment, an electronic device may include a power source configured to provide operational power to the electronic device and a processor coupled to the power source. The processor may be configured to generate temperature predictions using a model of a structure and possible control scenarios, determine a value of the temperature predictions and the respective possible control scenarios using a cost function, the cost function comprising weighted factors related to an error between a setpoint temperature and the temperature predictions, a length of runtime for an environmental control system (e.g., an HVAC system), and a length of environmental control system cycles. The processor may also be configured to select the control scenario with the highest value to apply to control the environmental control system. The control scenarios may be generated using upper confidence bound for trees (UCT).
Abstract:
The current application is directed to intelligent controllers that use sensor output and electronically stored information, including one or more of electronically stored rules, parameters, and instructions, 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 modify control schedules with respect to the presence and absence of the one or more entities. The intelligent controllers employ feedback information to continuously adjust the electronically stored parameters and rules in order to minimize the number of incorrect inferences with respect to the presence or absence of the one or more entities and in order to maximize the efficiency by which various types of systems controlled by the intelligent controllers carry out selected operational modes.