Based on the hierarchical model of SDI (Software-Defined Intelligence)

a system for action recognition during sleep is designed to deal with various changing factors in smart environment through rule-based reasoning. A time queue is designed to extract the characteristics of actions in real-time to train the model

and a rule extraction algorithm is proposed to extract the rules required by the system from the model. Depending on these rules

the proposed system can recognize nine types of sleep actions: The recognition precision of each type can exceed 96%; the total recognition accuracy can reach 98.9%. Importantly

it has more robust adaptability than other systems. Experimental results show that the system can update rules for quickly adapting to changes in node position

the number of nodes

and user requirements.