Old Man Behavior Recognition Method Based On Indoor Trajectory Analysis

In recent years,the degree of population aging has been deepened,the phenomenon of empty-nesters has become an urgent social problem.As the product of emerging technologies,remote monitoring system has unexampled advantages compared with the traditional service.It is of great significance to improve the life quality and ensure the safety of the elders by collecting and analyzing the individual behavior data,identifying the behavior intention and realizing the early warning of the abnormal behavior.Based on the analysis of the trajectory data in the indoor environment,the paper studies the daily behavior monitoring method for the elders.The main research contents are:Based on the trajectory data in the indoor environment,the user behavior model,the behavior-time model and the key point model are constructed as the basis of the trajectory analysis.This paper proposes a trajectory analysis method based on trajectory segmentation,using the minimum confidence interval to obtain the duration range.Through the setting of correlation coefficient and buffer coefficient,the influence of different external factors and indoor sensitivity on the behavior is discussed to improve the recognition accuracy of the real stay points in the trajectory sequence,and as the behavior recognition and abnormal behavior detection basis.The association template is established based on the trajectory data and the user's behavior for behavior identification and abnormal behavior detection.The successor key point behavior association template is added based on the position and time behavior association template,and a behavior recognition method based on template matching is proposed based on the established behavior association template.The relationship between the location,the time and the successor key point is established based on the weight;the behavior habits of the user is understood by the behavioral trajectory probabilistic analysis,and the behavior that is not occurring in the behavioral trajectory sequence is detected as an abnormal behavior.