Systems and methods are disclosed for the generation of more accurate usage profiles for use in the modeling of existing buildings. Building sensor data associated with individual rooms in a building can be decomposed using wavelets to identify features that correspond to heat loads generated by occupant presence and/or equipment operation. From this information, the occupancy state of individual rooms can be estimated. The estimated occupancy state for the individual rooms in the building then can be used to generate a usage profile for the building. The usage profile can be used to estimate current and/or future energy usage or costs or to control equipment in the building at a current and/or future time.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for predicting energy usage in a building, the method comprising: as implemented by a computer system comprising one or more computing devices, the computer system configured with specific executable instructions, receiving temperature data corresponding to a room in the building, wherein the temperature data comprises a plurality of temperature measurements taken at different respective points in time; analyzing the received temperature data in a time-scale domain; and estimating an occupancy state of the room in the building based on the analysis of the received temperature data, wherein the occupancy state of the room in the building indicates whether the room is occupied or vacant. 2. The method of claim 1, wherein analyzing the received temperature data comprises generating a time-frequency transformation of a temperature response of the room based on the received temperature data. 3. The method of claim 2, wherein the generated time-frequency transformation comprises an indication of a spectral energy in the room for a period of time. 4. The method of claim 3, further comprising: identifying first spectral energy in the room on a weekend during the period of time; and identifying second spectral energy in the room on a weekday during the period of time. 5. The method of claim 4, wherein estimating an occupancy state of the room comprises: comparing the first spectral energy and the second spectral energy; and identifying the room as being occupied on the weekday during the period of time in response to a determination that the first spectral energy is less than the second spectral energy. 6. The method of claim 1, further comprising: generating a usage profile for the building based on the estimated occupancy state; and transmitting a control signal to a building control unit based on the generated usage profile, wherein the control signal instructs the building control unit to set a temperature for the room based on a time of day. 7. The method of claim 6, further comprising generating a reference usage profile for the room based on operating hours of the building and observational data of occupant activity in the building. 8. The method of claim 7, wherein generating a usage profile for the building comprises modifying the reference usage profile based on the estimated occupancy state to generate the usage profile. 9. The method of claim 1, wherein the building comprises a second room in which second temperature data is not available. 10. The method of claim 9, further comprising: generating a probability mass function for the second room based on the estimated occupancy state, wherein the probability mass function comprises an estimation of an occupancy state of the second room; and generating a usage profile based on the estimated occupancy state of the room and the probability mass function for the second room. 11. The method of claim 1, wherein the building control unit comprises a heating ventilation air conditioning (HVAC) unit. 12. An electronic apparatus for predicting energy usage in a building comprising: a computer data repository configured to store a data set, the data set comprising building sensor data, the building sensor data comprising a plurality of values captured over time for a room in the building; and a computing system comprising one or more computing devices, the computing system in communication with the computer data repository and programmed to implement: a sensor data analyzer configured to retrieve and analyze the building sensor data; an occupancy estimator configured to estimate an occupancy state of the room in the building based on the analysis of the building sensor data; and a usage profile builder configured to generate a usage profile for the building based on the estimated occupancy state. 13. The electronic apparatus of claim 12, wherein the building sensor data comprises building temperature data. 14. The electronic apparatus of claim 13, wherein the sensor data analyzer is further configured to generate a time-frequency transformation of a temperature response of the room based on the building temperature data. 15. The electronic apparatus of claim 14, wherein the generated time-frequency transformation comprises an indication of a spectral energy in the room for a period of time. 16. The electronic apparatus of claim 15, wherein the sensor data analyzer is further configured to: identify first spectral energy in the room on a weekend during the period of time; and identify second spectral energy in the room on a weekday during the period of time. 17. The electronic apparatus of claim 16, wherein the occupancy estimator is further configured to: compare the first spectral energy and the second spectral energy; and identify the room as being occupied on the weekday during the period of time in response to a determination that the first spectral energy is less than the second spectral energy. 18. The electronic apparatus of claim 12, wherein the usage profile builder is further configured to generate a reference usage profile for the room based on operating hours of the building and observational data of occupant activity in the building. 19. The electronic apparatus of claim 18, wherein the usage profile builder is further configured to modify the reference usage profile based on the estimated occupancy state to generate the usage profile. 20. The electronic apparatus of claim 12, wherein the building comprises a second room in which building sensor data is not available. 21. The electronic apparatus of claim 20, wherein the usage profile builder is further configured to generate a probability mass function for the second room based on the estimated occupancy state, wherein the probability mass function comprises an estimation of an occupancy state of the second room. 22. The electronic apparatus of claim 21, wherein the usage profile builder is further configured to generate the usage profile based on the estimated occupancy state of the room and the probability mass function for the second room. 23. The electronic apparatus of claim 12, wherein the computing system is further programmed to implement a control system configured to transmit a control signal to a building control unit based on the generated usage profile, wherein the control signal causes the building control unit to adjust a temperature of the room 24. The electronic apparatus of claim 23, wherein the building control unit comprises a heating ventilation air conditioning (HVAC) unit. 25. A computer storage system comprising a non-transitory storage device, said computer storage system having stored thereon executable program instructions that direct a computer system to at least: receive building sensor data corresponding to a room in a building; analyze the received building sensor data; estimate an occupancy state of the room in the building based on the analysis of the received building sensor data; generate a usage profile for the building based on the estimated occupancy state; and generate a model of predicted energy consumption for the building based on the generated usage profile. 26. The computer storage system of claim 25, wherein the building sensor data comprises building temperature data. 27. The computer storage system of claim 26, wherein the executable program instructions further direct the computer system to at least generate a time-frequency transformation of a temperature response of the room based on the received temperature data. 28. The computer storage system of claim 27, wherein the generated time-frequency transformation comprises an indication of a spectral energy in the room for a period of time. 29. The computer storage system of claim 28, wherein the executable program instructions further direct the computer system to at least: identify first spectral energy in the room on a weekend during the period of time; and identify second spectral energy in the room on a weekday during the period of time. 30. The computer storage system of claim 29, wherein the executable program instructions further direct the computer system to at least: compare the first spectral energy and the second spectral energy; and identify the room as being occupied on the weekday during the period of time in response to a determination that the first spectral energy is less than the second spectral energy. 31. The computer storage system of claim 25, wherein the executable program instructions further direct the computer system to at least generate a reference usage profile for the room based on operating hours of the building and observational data of occupant activity in the building. 32. The computer storage system of claim 31, wherein the executable program instructions further direct the computer system to at least modify the reference usage profile based on the estimated occupancy state to generate the usage profile. 33. The computer storage system of claim 25, wherein the building comprises a second room in which second temperature data is not available. 34. The computer storage system of claim 33, wherein the executable program instructions further direct the computer system to at least: generate a probability mass function for the second room based on the estimated occupancy state, wherein the probability mass function comprises an estimation of an occupancy state of the second room; and generate the usage profile based on the estimated occupancy state of the room and the probability mass function for the second room.