Abstract:In order to timely monitoring of drug circulation market for relevant departments to strengthen drug quality supervision Currently, IoT technology has been introduced in pharmaceutical cold chain logistics, but there are many links in the pharmaceutical cold chain logistics and the risk uncertainty of each link will shift with time. Therefore, the risk of each link of pharmaceutical cold chain logistics in the IoT environment is firstly analyzed by flow chart method to analyze the many factors causing the risks of each link, and the entropy weight method is used to objectively empower the risk indicators to establish a risk factor evaluation index system, and then use the GeNIe software. Establish a dynamic Bayesian network model to evaluate the risk of key risk factors in the risk link. The results show that the risk of transportation link has the highest probability of occurrence in risk assessment, and the verification of equipment selection is the key risk factor affecting IoT pharmaceutical cold chain, which provides a basis for companies and governments to control drug quality and safety management.