The invention discloses a traffic supervision
system applied to an intelligent street lamp and an intelligent supervision method thereof, relates to the technical field of intelligent traffic, and solves the problems that an existing intelligent street lamp
system lacks a physical-
digital mapping relation,
edge computing resource allocation is low in efficiency and
cloud computing delay is high. According to the scheme, on the basis of multi-sensor data fusion, space-time reference unification is carried out by adopting an
atomic clock and a GNSS, and a dynamic causal graph is constructed through a graph neural network, so that abnormal event detection is optimized; an improved Jaccard space-time similarity
algorithm is adopted to optimize calculation task allocation, an edge calculation cluster is constructed based on 5G-V2X, and high-risk region identification and
traffic flow prediction are carried out; a LiFi or 5G-UWB communication medium is adaptively selected through a multi-
modal fusion
reinforcement learning algorithm, and efficient early warning information synchronization is realized; according to the method, the multi-
source data fusion value and the early warning precision are remarkably improved, the computing power
resource utilization rate is optimized, and the instruction real-time performance and the
system self-adaptive capability in a complex environment are enhanced.