Research on the Prediction-Based Clustering Method in the Community of Medical Vehicles for Connected Health

Combined with the Internet of Vehicles, some intelligent systems for connected health can make medical vehicles transport medical supplies more safely and timely in response to catastrophic natural disasters or serious accidents. However, in an urban scenario, the crisscrossing of roads and the uneven distribution of vehicles exist, which lead to problems such as the high mobility of vehicles and the attachment of data. These have become important contributors to the low stability of the vehicle community and the high distortion of the data among medical vehicles. Focusing on the above problems, this paper proposes a prediction-based multirole classification community clustering method (PMRC) for the vehicular ad hoc network (VANET). The experimental results show that the method can effectively improve the stability of the community in VANET and reduce the probability of data distortion.