In order to estimate behavior of a person at home from a feature and a power consumption pattern of an electrical device, an on-demand power control system of the present invention includes initial human-induced probability value estimation means that estimates a state of the electrical device, and estimates an initial value of a human-induced probability of the electrical device based on the estimated state of the electrical device, human position estimation means for calling up the initial value of the human-induced probability of the electrical device and a likelihood map of this device from a memory, performing, for all samples, a process of referring to a sample human position selected from the likelihood map and calculating a weight of the device by multiplying a human position and the human-induced probability of the device, and estimating a probability of a human position at each time point until a final time; and human-induced probability re-estimation means for performing recalculation of the human-induced probability based on the human-induced probability and a human position probability, performing the recalculation of the human-induced probability until a value of the recalculation converges, and outputting the human-induced probability and the human position probability when the value converges.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An on-demand power control system comprising a power source including at least a commercial power source, a plurality of electrical devices, a smart tap connected to the electrical devices, a human behavior estimation apparatus, including a memory, for estimating behavior of a person in a living space, and a network to which the human behavior estimation apparatus is connected via the smart tap, wherein the human behavior estimation apparatus includes initial human-induced probability value estimation means for comparing a feature obtained from a power consumption pattern of an electrical device with a feature of learning data obtained in advance for each electrical device to estimate a state of the electrical device, and estimating an initial value of a human-induced probability of the electrical device based on the estimated state of the electrical device, human position estimation means for calling up the initial value of the human-induced probability of the electrical device and a likelihood map of the device from the memory, performing a process, for all samples, of referring to a sample human position selected from the likelihood map and calculating a weight of the device by multiplying the human position and the human-induced probability of the device, and estimating a probability of a human position at each time point until a final time, and human-induced probability re-estimation means for performing recalculation of the human-induced probability based on the human-induced probability and a human position probability, performing the recalculation of the human-induced probability until a value of the recalculation converges, and outputting the human-induced probability and the human position probability when the value is converged. 2. The on-demand power control system according to claim 1, wherein the human behavior estimation apparatus estimates the behavior of a person based on the human-induced probability that is a probability of a person performing a human-induced operation on a device and the human position probability that is a probability of a person existing at a position. 3. The on-demand power control system according to claim 2, wherein the human behavior estimation apparatus determines feature data of an operation state based solely on the power consumption pattern of each electrical device, and determines the human position and the human-induced probability by repeated calculation while taking a human-induced probability obtained from the data as an initial value, to estimate both the human position and the human-induced probability. 4. The on-demand power control system according to claim 3, wherein the feature data of an operation state is composed of an id of an electrical device, an operation state of the device, and a feature of the device. 5. The on-demand power control system according to claim 4, wherein the power consumption pattern of an electrical device is generated based on a change in an operation mode or a state of an electrical device due to operation of the device by a sequence of human states including movement and stopping. 6. The on-demand power control system according to claim 4, wherein the feature of an electrical device is an average and dispersion of power consumption. 7. The on-demand power control system according to claim 1, wherein the initial human-induced probability value estimation means is capable of estimating the initial value of the human-induced probability based on a probability of a state of an electrical device, by having a probability of a state shift of the electrical device being caused by a human-induced operation given in advance. 8. The on-demand power control system according to claim 1, wherein the human position estimation means estimates a movement position of a person based on a human-induced probability according to which a two-dimensional position of the person at a time t may be determined by repeated calculation for a preceding time t−1. 9. The on-demand power control system according to claim 8, wherein the human position estimation means uses a time-series filter to estimate the human position probability. 10. The on-demand power control system according to claim 9, wherein the time-series filter is a particle filter, a Kalman filter or a moving average filter. 11. The on-demand power control system according to any one of claims 8 to 10, wherein the human position estimation means calculates the human-induced probability by using a likelihood map that is based on a relationship between a position of an electrical device and a human position. 12. The on-demand power control system according to claim 11, wherein the likelihood map shows, by using a pixel value, an existence probability of a person who is capable of pressing a power switch of an electrical device, based on a use status of the electrical device in an actual living space. 13. The on-demand power control system according to claim 12, wherein, in the likelihood map, calculation is performed using a pixel value of zero for a range that cannot be reached by a human hand if there is an obstacle. 14. The on-demand power control system according to claim 12, wherein, in the likelihood map, small pixel values are assigned to a wide range in a case where the electrical device may be operated by a remote control. 15. The on-demand power control system according to claim 12, wherein, in the likelihood map, in a case where the electrical device may be operated from a plurality of positions, large pixel values are assigned to a plurality of narrow ranges allowing operation. 16. The on-demand power control system according to claim 13, wherein, in the likelihood map, the pixel values are expressed based on a floor plan, the obstacle, position/distance of a power switch, and a position of the electrical device. 17. The on-demand power control system according to claim 16, wherein, in a case where there are a plurality of persons, the human behavior estimation apparatus performs calculation using a mixed normal distribution for the number of persons. 18. A program for causing a computer to operate as a human behavior estimation apparatus on an on-demand power control system including a power source including at least a commercial power source, a plurality of electrical devices, a smart tap connected to the electrical devices, the human behavior estimation apparatus, including a memory, for estimating behavior of a person in a living space, and a network to which the human behavior estimation apparatus is connected via the smart tap, wherein the human behavior estimation apparatus includes initial human-induced probability value estimation means, human position estimation means, and human-induced probability re-estimation means, and wherein the program causes the computer to perform processes of: by the initial human-induced probability value estimation means, comparing a feature obtained from a power consumption pattern of an electrical device with a feature of learning data obtained in advance for each electrical device to estimate a state of the electrical device, and calculating an estimation of an initial value of a human-induced probability of the electrical device based on the estimated state of the electrical device, by the human position estimation means, calling up the initial value of the human-induced probability of the electrical device and a likelihood map of the device from the memory, performing, for all samples, a process of referring to a sample human position selected from the likelihood map and calculating a weight of the device by multiplying a human position and the human-induced probability of the device, and calculating an estimation of a probability of a human position at each time point until a final time, and by the human-induced probability re-estimation means, performing recalculation of the human-induced probability based on the human-induced probability and a human position probability, performing the recalculation of the human-induced probability until a value of the recalculation converges, and outputting the human-induced probability and the human position probability when the value is converged. 19. A program for causing a computer to operate as a human behavior estimation apparatus according to claim 1, the program causing the computer to perform a process of: estimating, behavior of a person based on a human-induced probability that is a probability of a person performing a human-induced operation on a device and a human position probability that is a probability of a person existing at a position. 20. A program for causing a computer to operate as a human behavior estimation apparatus according to claim 1, the program causing the computer to perform a process of: determining feature data of an operation state based solely on a power consumption pattern of each electrical device, and determining a human position and a human-induced probability by repeated calculation while taking a human-induced probability obtained from the data as an initial value, to estimate both the human position and a human-induced operation. 21. A computer-readable recording medium recording a program according to claim 18. 22. A computer-readable recording medium recording a program according to claim 19. 23. A computer-readable recording medium recording a program according to claim 20.