Abstract: Techniques are generally described for fusing sensor data of different modalities using a transformer. In various examples, first sensor data may be received from a first sensor and second sensor data may be received from a second sensor. A first feature representation of the first sensor data may be generated using a first machine learning model and a second feature representation of the second sensor data may be generated using a second machine learning model. In some examples, a modified first feature representation of the first sensor data may be generated based at least in part on a self-attention mechanism of a transformer encoder. The modified first feature representation may be generated based at least in part on the first feature representation and the second feature representation. A computer vision task may be performed using the modified first feature representation.

Abstract: Systems and methods are provided for predicting a traversal time for a route. A request for navigation directions is received and a route between the origin and destination is calculated. A series of route segments to be traversed on the route are identified, as well as one or more sub-series of route segments of the series of route segments, with each sub-series having route segments to be traversed consecutively on a portion of the route. For each sub-series, a sub-series traversal time is predicted based on historical traversal time data associated with historical trips where each of the route segments of the sub-series were traversed consecutively. A total route traversal time is predicted based on the sub-series traversal time. A set of navigation directions and the predicted total route traversal time are provided for presentation on a client device for navigating from the origin to the destination via the route.

Abstract: Systems and methods are provided for predicting a traversal time for a route. A request for navigation directions is received and a route between the origin and destination is calculated. A series of route segments to be traversed on the route are identified, as well as one or more sub-series of route segments of the series of route segments, with each sub-series having route segments to be traversed consecutively on a portion of the route. For each sub-series, a sub-series traversal time is predicted based on historical traversal time data associated with historical trips where each of the route segments of the sub-series were traversed consecutively. A total route traversal time is predicted based on the sub-series traversal time. A set of navigation directions and the predicted total route traversal time are provided for presentation on a client device for navigating from the origin to the destination via the route.

Abstract: Systems and Methods disclosed herein relate to providing a message to an application programming interface (API). The message includes a request for data from a data model, a submission of data to the data model, or both; and a host selection between: a representational state transfer (REST) host and a subscription-based application programming interface (API) host, wherein the REST host receives REST-based messages and the subscription-based API host receives messages in accordance with a standard of the subscription-based API host; wherein the request for data, the submission of data, or both are configured to create, delete, modify, or any combination thereof data related to a smart-device environment structure, a thermostat, a hazard detector, or any combination thereof stored in a data model accessible by the API.

Abstract: A thermostat my include a stored setpoint schedule, temperature sensors providing temperature sensor measurements; and a processing system configured to control an HVAC system based at least in part on the setpoint temperature and the temperature sensor measurements. The processing system may be configured to control the HVAC system by receiving an indication of a first time interval, where energy is available to the HVAC system at a first rate during the first time interval, energy is available to the HVAC system at a second rate during a second time interval that is outside of the first time interval, and the first rate is higher than the second rate; identifying a first one or more setpoints in the plurality of setpoints of the stored setpoint schedule that occur in the first time interval; and decreasing a temperature component of at least one of the first one or more setpoints.

Abstract: A thermostat may include one or more memory devices comprising a stored setpoint schedule, one or more temperature sensors configured to provide temperature sensor measurements, and a processing system configured to be in operative communication the one or more memory devices to determine a setpoint temperature, and in still further operative communication with a heating, ventilation, and air conditioning (HVAC) system to control the HVAC system based at least in part on the setpoint temperature and the temperature sensor measurements. The processing system may be configured to control the HVAC system by receiving an indication that a total instantaneous energy usage rate for a structure in which the thermostat is installed is projected to exceed a threshold amount; and altering the stored setpoint schedule to reduce an energy usage rate of the HVAC system.

Abstract: Systems and techniques are provided for learned overrides for home security. A sensor of a security system may be armed. A trip signal may be received indicating a tripping of the sensor. It may be determined that the trip signal can be automatically overridden based on matching an identity of the sensor and a state of the security system with a pattern in a model. The pattern may represent a state of the security system in which automatically overriding the trip signal from the sensor is permitted. The trip signal from the sensor may be automatically overridden without input from a user.

Abstract: A thermostat may be programmed to operate during cold-weather months by operating in a heat mode where the thermostat periodically causes the HVAC system to activate a heating function to heat an enclosure based at least in part on the stored setpoint schedule; receiving an indication from a thermostat management server of a demand response event while the thermostat is operating in the heat mode; determining whether the thermostat stores a user setting indicating that the thermostat should preheat the enclosure prior to reaching a scheduled setpoint in the stored setpoint schedule; and preheating the enclosure prior to the demand response event based on a determination that the thermostat stores the user setting indicating that the thermostat should preheat the enclosure prior to reaching the scheduled setpoint in the stored setpoint schedule.

Abstract: Systems and techniques are provided for learned overrides for home security. A sensor of a security system may be armed. A trip signal may be received indicating a tripping of the sensor. It may be determined that the trip signal can be automatically overridden based on matching an identity of the sensor and a state of the security system with a pattern in a model. The pattern may represent a state of the security system in which automatically overriding the trip signal from the sensor is permitted. The trip signal from the sensor may be automatically overridden without input from a user.

Abstract: A thermostat may be programmed to operate during cold-weather months by operating in a heat mode where the thermostat periodically causes the HVAC system to activate a heating function to heat an enclosure based at least in part on the stored setpoint schedule; receiving an indication from a thermostat management server of a demand response event while the thermostat is operating in the heat mode; determining whether the thermostat stores a user setting indicating that the thermostat should preheat the enclosure prior to reaching a scheduled setpoint in the stored setpoint schedule; and preheating the enclosure prior to the demand response event based on a determination that the thermostat stores the user setting indicating that the thermostat should preheat the enclosure prior to reaching the scheduled setpoint in the stored setpoint schedule.

Abstract: In an embodiment, an electronic device may include storage containing processor-executable instructions and a current setpoint schedule, and a processor configured to execute the instructions.

Abstract: Systems and techniques are provided for learned overrides for home security. A sensor of a security system may be armed. A trip signal may be received indicating a tripping of the sensor. It may be determined that the trip signal can be automatically overridden based on matching an identity of the sensor and a state of the security system with a pattern in a model. The pattern may represent a state of the security system in which automatically overriding the trip signal from the sensor is permitted. The trip signal from the sensor may be automatically overridden without input from a user.

Abstract: A thermostat my include a stored setpoint schedule, temperature sensors providing temperature sensor measurements; and a processing system configured to control an HVAC system based at least in part on the setpoint temperature and the temperature sensor measurements. The processing system may be configured to control the HVAC system by receiving an indication of a first time interval, where energy is available to the HVAC system at a first rate during the first time interval, energy is available to the HVAC system at a second rate during a second time interval that is outside of the first time interval, and the first rate is higher than the second rate; identifying a first one or more setpoints in the plurality of setpoints of the stored setpoint schedule that occur in the first time interval; and decreasing a temperature component of at least one of the first one or more setpoints.

Abstract: A thermostat may include one or more memory devices comprising a stored setpoint schedule, one or more temperature sensors configured to provide temperature sensor measurements, and a processing system configured to be in operative communication the one or more memory devices to determine a setpoint temperature, and in still further operative communication with a heating, ventilation, and air conditioning (HVAC) system to control the HVAC system based at least in part on the setpoint temperature and the temperature sensor measurements. The processing system may be configured to control the HVAC system by receiving an indication that a total instantaneous energy usage rate for a structure in which the thermostat is installed is projected to exceed a threshold amount; and altering the stored setpoint schedule to reduce an energy usage rate of the HVAC system.

Abstract: A peer group of a user may be identified on the basis of geographic information and building occupancy information for the user and for possible peers of the user. Energy usage data for each peer group member may be compared with that of the user. A comparison result may be computed between each peer group member and the user. A representation of comparison results may be provided to the user.

Abstract: Systems and Methods disclosed herein relate to providing a message to an application programming interface (API). The message includes a request for data from a data model, a submission of data to the data model, or both; and a host selection between: a representational state transfer (REST) host and a subscription-based application programming interface (API) host, wherein the REST host receives REST-based messages and the subscription-based API host receives messages in accordance with a standard of the subscription-based API host; wherein the request for data, the submission of data, or both are configured to create, delete, modify, or any combination thereof data related to a smart-device environment structure, a thermostat, a hazard detector, or any combination thereof stored in a data model accessible by the API.

Abstract: A peer group of a user may be identified on the basis of geographic information and building occupancy information for the user and for possible peers of the user. Energy usage data for each peer group member may be compared with that of the user. A comparison result may be computed between each peer group member and the user. A representation of comparison results may be provided to the user.

Abstract: This patent specification relates to systems and methods for coordinating energy use of disparately-controlled devices based on modeling characteristics of an enclosure. More particularly, this patent specification relates to enabling third party vendors to coordinate operation of third party devices existing within the enclosure with the enclosure's building control system to manage energy consumption.

Abstract: Systems and techniques are provided for learned overrides for home security. A sensor of a security system may be armed. A trip signal may be received indicating a tripping of the sensor. It may be determined that the trip signal can be automatically overridden based on matching an identity of the sensor and a state of the security system with a pattern in a model. The pattern may represent a state of the security system in which automatically overriding the trip signal from the sensor is permitted. The trip signal from the sensor may be automatically overridden without input from a user.

Abstract: This patent specification relates to systems and methods for modeling characteristics of an enclosure. More particularly, this patent specification relates to thermal modeling of internal temperature dynamics of the enclosure.