Abstract: A system for detecting occupancy of an enclosure may include a sensing system adapted to monitor utility information for the enclosure which tends to indicate a likelihood of occupancy of the enclosure. The utility information may include power line information, Smart Meter information, Wi-Fi information, etc. The system may also include a processing system programmed to estimate occupancy of the enclosure based at least in part on the monitored utility information by the sensing system.

Abstract: Modeling the behavior of an enclosure for use by a control system of an HVAC system is described. A model for the enclosure that describes the enclosure's behavior for use by the control system is updated based on weather forecast data. The weather forecast data can include predictions more than 24 hours in the future, and can include predictions on temperature, humidity and/or dew point, solar output, precipitation. The model for the enclosure can also be updated based on additional information and data. The model for the enclosure can be updated based also on an enclosure model stored in a database, and/or enclosure information from a user. The model can be updated based on active testing of the enclosure which can be performed automatically or in response to user input. The testing can include heating and/or cooling the enclosure at times when the enclosure is not likely occupied.

Abstract: A system for detecting occupancy of an enclosure may include a sensing system adapted to monitor utility information for the enclosure which tends to indicate a likelihood of occupancy of the enclosure. The utility information may include power line information, Smart Meter information, Wi-Fi information, etc. The system may also include a processing system programmed to estimate occupancy of the enclosure based at least in part on the monitored utility information by the sensing system.

Abstract: Systems and methods are described for predicting and/or detecting occupancy of an enclosure, such as a dwelling or other building, which can be used for a number of applications. An a priori stochastic model of occupancy patterns based on information of the enclosure and/or the expected occupants of the enclosure is used to pre-seed an occupancy prediction engine. Along with data from an occupancy sensor, the occupancy prediction engine predicts future occupancy of the enclosure. Various systems and methods for detecting occupancy of an enclosure, such as a dwelling, are also described.

Abstract: Modeling the behavior of an enclosure for use by a control system of an HVAC system is described. A model for the enclosure that describes the enclosure's behavior for use by the control system is updated based on weather forecast data. The weather forecast data can include predictions more than 24 hours in the future, and can include predictions on temperature, humidity and/or dew point, solar output, precipitation. The model for the enclosure can also be updated based on additional information and data. The model for the enclosure can be updated based also on an enclosure model stored in a database, and/or enclosure information from a user. The model can be updated based on active testing of the enclosure which can be performed automatically or in response to user input. The testing can include heating and/or cooling the enclosure at times when the enclosure is not likely occupied.

Abstract: Systems and methods are described for predicting and/or detecting occupancy of an enclosure, such as a dwelling or other building, which can be used for a number of applications. An a priori stochastic model of occupancy patterns based on information of the enclosure and/or the expected occupants of the enclosure is used to pre-seed an occupancy prediction engine. Along with data from an occupancy sensor, the occupancy prediction engine predicts future occupancy of the enclosure. Various systems and methods for detecting occupancy of an enclosure, such as a dwelling, are also described.

Abstract: Modeling the behavior of an enclosure for use by a control system of an HVAC system is described. A model for the enclosure that describes the enclosure's behavior for use by the control system is updated based on weather forecast data. The weather forecast data can include predictions more than 24 hours in the future, and can include predictions on temperature, humidity and/or dew point, solar output, precipitation. The model for the enclosure can also be updated based on additional information and data. The model for the enclosure can be updated based also on an enclosure model stored in a database, and/or enclosure information from a user. The model can be updated based on active testing of the enclosure which can be performed automatically or in response to user input. The testing can include heating and/or cooling the enclosure at times when the enclosure is not likely occupied.

Abstract: Systems and methods are described for predicting and/or detecting occupancy of an enclosure, such as a dwelling or other building, which can be used for a number of applications. An a priori stochastic model of occupancy patterns based on information of the enclosure and/or the expected occupants of the enclosure is used to pre-seed an occupancy prediction engine. Along with data from an occupancy sensor, the occupancy prediction engine predicts future occupancy of the enclosure. Various systems and methods for detecting occupancy of an enclosure, such as a dwelling, are also described.

Abstract: Systems and methods for modeling the behavior of an enclosure for use by a control system of an HVAC system are described. A model for the enclosure that describes the behavior of the enclosure for use by the control system is updated based on a weather forecast data. The weather forecast data can include predictions more than 24 hours in the future, and can include predictions such as temperature, humidity and/or dew point, solar output, precipitation. The model for the enclosure can also be updated based on additional information and data such as historical weather data such as temperature, humidity, wind, solar output and precipitation, occupancy data, such as predicted and/or detected occupancy data, calendar data, and data from the one or more weather condition sensors that sense current parameters such as temperature, humidity, wind, precipitation, and/or solar output.

Abstract: Systems and methods are described for predicting and/or detecting occupancy of an enclosure, such as a dwelling or other building, which can be used for a number of applications. An a priori stochastic model of occupancy patterns based on information of the enclosure and/or the expected occupants of the enclosure is used to pre-seed an occupancy prediction engine. Along with data from an occupancy sensor, the occupancy prediction engine predicts future occupancy of the enclosure. Various systems and methods for detecting occupancy of an enclosure, such as a dwelling, are also described.

Abstract: Systems and methods are described for predicting and/or detecting occupancy of an enclosure, such as a dwelling or other building, which can be used for a number of applications. An a priori stochastic model of occupancy patterns based on information of the enclosure and/or the expected occupants of the enclosure is used to pre-seed an occupancy prediction engine. Along with data from an occupancy sensor, the occupancy prediction engine predicts future occupancy of the enclosure. Various systems and methods for detecting occupancy of an enclosure, such as a dwelling, are also described.

Abstract: Systems and methods for modeling the behavior of an enclosure for use by a control system of an HVAC system are described. A model for the enclosure that describes the behavior of the enclosure for use by the control system is updated based on a weather forecast data. The weather forecast data can include predictions more than 24 hours in the future, and can include predictions such as temperature, humidity and/or dew point, solar output, precipitation. The model for the enclosure can also be updated based on additional information and data such as historical weather data such as temperature, humidity, wind, solar output and precipitation, occupancy data, such as predicted and/or detected occupancy data, calendar data, and data from the one or more weather condition sensors that sense current parameters such as temperature, humidity, wind, precipitation, and/or solar output.

Abstract: Systems and methods are described for predicting and/or detecting occupancy of an enclosure, such as a dwelling or other building, which can be used for a number of applications. An a priori stochastic model of occupancy patterns based on information of the enclosure and/or the expected occupants of the enclosure is used to pre-seed an occupancy prediction engine. Along with data from an occupancy sensor, the occupancy prediction engine predicts future occupancy of the enclosure. Various systems and methods for detecting occupancy of an enclosure, such as a dwelling, are also described.