Given the popularity of smart environment in a hospital involving the participation of a large group of patients,scheduling of patients towards their desired destination is still being a challenging issue.With the development of Internet of Things(Io T),smart environments are increasingly being deployed in various public scenarios and in particular,hospitals are an important target environment for smart environments.This paper models a dynamic scheduling policy based on a patient flow scenario in order to solve the queuing issue and facilitate people’s experience.The dynamic scheduling policy aims to forward incoming patients to dissolve jams especially at the peaks by giving accurate predication of appointment time.The main modelling technique is a formal method—Performance evaluation process algebra(PEPA).The findings show that the dynamic scheduling policy is able to efficiently improve the patient flow. Given the popularity of smart environment in a hospital involving the participation of a large group of patients, scheduling of patients towards their desired destination still still a challenging issue .With the development of Internet of Things (Io T), smart environments are increasingly being deployed in various public scenarios and in particular, hospitals are an important target environment for smart environments. This paper models a dynamic scheduling policy based on a patient flow scenario in order to solve the queuing issue and facilitate people’s experience. dynamic over policy policies aims to forward incoming patients to dissolve jams especially at the peaks by gave accurate predication of appointment time. The main modeling technique is a formal method-Performance evaluation process algebra (PEPA) .The findings show that the dynamic scheduling policy is able to efficiently improve the patient flow.