Urban safety accident source tracking and risk pre-warning method based on Internet of things

An urban safety accident source tracking and risk pre-warning method based on the Internet of things comprises the following steps that (1) an urban safety accident source tracking application model is established, data collection comprises the operation that real-time monitoring is carried out on the on-site situations of urban safety accidents based on the RFID technology in the Internet of things, and network accessing comprises the operations that information of all links of the accidents is recorded in real time by using the RFID technology, and process data information is uploaded to a platform data sharing center; (2) a safety accident finite-state machine model is established; (3) clustering analysis is carried out on safety accident source tracking time series data; (4) pre-warning is carried out on the urban safety accidents based on a hidden semi Markov model (HSMM), wherein the state space of the HSMM of the safety pre-warning only comprises two states which are a safe sate and a crisis state, and the observation value of every time of the system behavior can belong to the safe state or can be the crisis state. The urban safety accident source tracking and risk pre-warning method based on the Internet of things is capable of effectively solving the problem of tracking, locating and pre-warning difficulty of the urban safety accidents and high in intelligent degree.