A method for counting a number of people based on appliance usages and a monitoring system using the same method. The method includes the following steps: collecting first numbers of people and first appliance usages corresponding to a first time duration in a specific space; establishing a predictive model related to the first time duration according to the first numbers of people and the appliance usages; detecting a second appliance usages in a second time duration; predicting a second number of people corresponding to the second time duration and the second appliance usages according to the predictive model.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for counting the number of people based on appliance usages, adapted for a monitoring system, comprising: collecting a plurality of first numbers of people and a plurality of first appliance usages corresponding to a first time duration in a specific space; establishing a predictive model related to the first time duration based on the plurality of first numbers of people and the plurality of first appliance usages; detecting a second appliance usage in a second time duration; and predicting a second number of people corresponding to the second time duration and the second appliance usage based on the predictive model. 2. The method as claimed in claim 1, wherein the step of establishing the predictive model related to the first time duration based on the plurality of first numbers of people and the plurality of first appliance usages comprises: executing an artificial neural network algorithm based on the plurality of first numbers of people and the plurality of first appliance usages to generate a plurality of weights and a plurality of offsets corresponding to a plurality of neurons in an artificial neural network; and establishing the predictive model based on the weights and the offsets. 3. The method as claimed in claim 2, wherein the step of predicting the second number of people corresponding to the second time duration and the second appliance usage based on the predictive model comprises: inputting the second appliance usage to the predictive model to calculate the second number of people based on the weights and the offsets. 4. The method as claimed in claim 1, wherein the step of establishing the predictive model related to the first time duration based on the plurality of first numbers of people and the plurality of first appliance usages comprises: inputting the plurality of first numbers of people and the plurality of first appliance usages to a support vector machine to find a classifier that classifies the plurality of first numbers of people and the plurality of first appliance usages; and establishing the predictive model based on the classifier. 5. The method as claimed in claim 4, wherein the step of predicting the second number of people corresponding to the second time duration and the second appliance usage based on the predictive model comprises: inputting the second appliance usage to the predictive model to find the second number of people corresponding to the second appliance usage based on the classifier. 6. The method as claimed in claim 1, further comprising: generating a power analysis report and providing a power usage suggestion based on the plurality of first numbers of people, the plurality of first appliance usages, the second appliance usage, and the second number of people. 7. A monitoring system, comprising: a detecting device, collecting a plurality of first numbers of people and a plurality of first appliance usages corresponding to a first time duration in a specific space; and a computer device, coupled to the detecting device, the computer device comprising: a storage unit, storing a plurality of modules; and a processing unit, coupled to the storage unit, accessing and executing the plurality of modules recorded in the storage unit, wherein the plurality of modules comprise: a model establishing module, establishing a predictive model related to the first time duration based on the plurality of first numbers of people and the plurality of first appliance usages; a detecting module, controlling the detecting device to detect a second appliance usage in a second time duration; and a predicting module, predicting a second number of people corresponding to the second time duration and the second appliance usage based on the predictive model. 8. The system as claimed in claim 7, wherein the model establishing module is configured to: executing an artificial neural network algorithm based on the plurality of first numbers of people and the plurality of first appliance usages to generate a plurality of weights and a plurality of offsets corresponding to a plurality of neurons in an artificial neural network; and establish the predictive model based on the weights and the offsets. 9. The system as claimed in claim 8, wherein the predictive module inputs the second appliance usage to the predictive model to calculate the second number of people based on the weights and the offsets. 10. The system as claimed in claim 7, wherein the model establishing module is configured to: input the plurality of first numbers of people and the plurality of first appliance usages to a classifier that classifies the plurality of first numbers of people and the plurality of first appliance usages; and establish the predictive model based on the classifier. 11. The system as claimed in claim 10, wherein the predictive module inputs the second appliance usage to the predictive model to find the second number of people corresponding to the second appliance usage based on the classifier. 12. The system as claimed in claim 7, wherein the predictive module further generates a power analysis report and provides a power usage suggestion based on the plurality of first numbers of people, the plurality of first appliance usages, the second appliance usage, and the second number of people. 13. A method for counting the number of people based on appliance usages, adapted for a monitoring system, comprising: converting a plurality of first appliance types corresponding to a first time duration in a plurality of first spaces and respective first appliance numbers of the plurality of first appliance types into a plurality of training vectors, wherein the plurality of first spaces correspond to a specific space; converting a plurality of second appliance types corresponding to the first time duration in the specific space and respective second appliance numbers of the plurality of second appliance types into a testing vector; generating a maximal testing vector based on the plurality of training vectors and the testing vector, wherein the maximal testing vector comprises a plurality of elements, and the elements respectively correspond to the plurality of first appliance types; finding a plurality of specific elements that are not 0 from the plurality of elements; retrieving a plurality of first appliance usages corresponding to each of the specific elements, wherein the first appliance usages correspond to a plurality of first numbers of people; executing a principal component analysis on the plurality of first appliance usages corresponding to each of the specific elements to respectively find a principal components of the plurality of first appliance usages; inputting the principal component of each of the plurality of first appliance usages to a support vector machine to find a classifier that classifies the principal component of each of the first appliance usages; detecting a second appliance usage in a second time duration; and finding a second number of people corresponding to the second appliance usage based on the classifier. 14. The method as claimed in claim 13, further comprising: generating a power analysis report and providing a power usage suggestion based on the plurality of first numbers of people, the plurality of first appliance usages, the second appliance usage, and the second number of people. 15. A monitoring system, comprising: a detecting device; and a computer device, coupled to the detecting device, the computer device comprising: a storage unit, storing a plurality of modules; and a processing unit, coupled to the storage unit, accessing and executing the plurality of modules recorded in the storage unit, wherein the plurality of modules comprise: a first converting module, converting a plurality of first appliance types corresponding to a first time duration in a plurality of first spaces and respective first appliance numbers of the plurality of first appliance types into a plurality of training vectors, wherein the plurality of first spaces correspond to a specific space; a second converting module, converting a plurality of second appliance types corresponding to the first time duration in the specific space and respective second appliance numbers of the plurality of second appliance types into a testing vector; a generating module, generating a maximal testing vector based on the plurality of training vectors and the testing vector, wherein the maximal testing vector comprises a plurality of elements, and the elements respectively correspond to the plurality of first appliance types; a searching module, finding a plurality of specific elements that are not 0 from the plurality of elements; an appliance usage retrieving module, retrieving a plurality of first appliance usages corresponding to each of the plurality of specific elements; an analysis module, executing a principal component analysis on the plurality of first appliance usages corresponding to each of the specific elements to respectively find a principal components of each of the plurality of first appliance usages, wherein the plurality of first appliance usages correspond to the plurality of first numbers of people; a classifying module, inputting the principal component of each of the plurality of first appliance usages to a classifier that classifies the principal component of each of the first appliance usages; a detecting module, controlling the detecting device to detect a second appliance usage in a second time duration; and a predicting module, predicting a second number of people corresponding to the second appliance usage based on the classifier. 16. The system as claimed in claim 15, wherein the predictive module further generates a power analysis report and provides a power usage suggestion based on the plurality of first numbers of people, the plurality of first appliance usages, the second appliance usage, and the second number of people.