Identify the needs of people with disabilities to form a behavioral model for the automatic operation of smart homes with methods based on support vector machine

This study detects the activity of disabled people living in smart homes based on monitoring their behavior and desires to achieve the final model and store it in the database of the building management system for decision making and automatic operation of equipment used to meet the needs of residents. First, a suitable set of sensors are installed to record and process data correctly in different parts of the building and some to control vital signs depending on the type of disability are installed on the body. . First: selecting sensors and implementing recording techniques, and focusing on the major activities of people with disabilities in smart homes, second: classifying and processing the data collected using the support vector machine (svm) algorithm; svm was performed using the optimal data congestion algorithm (pso) and finally the final pattern for storage in the building management system database.