The proposed investigation implies a state-of-theart design of a real-time system, which is optimized by AI, adopts AMQP, NNPC, and DES. The Advanced Message Queuing Protocol ensures not only low latency but also reliability in the communication process, Neural Network Predictive Control enables us to adjust predictive control according to the changes in the nonlinear environment, and the Discrete Event Simulation enables us to perform performance analysis and optimise decisions based on the simulation. The suggested framework is experimented with the help of discrete-event simulation, which implements the simulation of event flow and system dynamics in real time. The comparison and evaluation of the performance with the traditional ones, which include Agent-driven modelling, hybrid prediction management, and Constrained Application Protocol communications, is conducted in terms of model performance and evaluation criteria. According to the findings of the simulation, it is possible to provide high performance proposed Advanced Message Queuing Protocol – Neural Network Predictive Control – Discrete Event Simulation system demonstrates its efficiency and effectiveness even in real-time operational conditions.