Utilizing intelligent navigation systems necessitates the development of effective methods for assessing road conditions. This comprises real-time root data collection from the road network and forecasting the evolution of route characteristics, which are frequently dependent on incomplete or erroneous data from vehicle detectors. This article presents an overview of the imputation capabilities of artificial immune systems that are suited for future Internet services allowed by OpenFlow. OpenFlow technology enables network operations, protocol segmentation, and an integrated management layer in routers and switches. OpenFlow enables major changes in the behavior of the networks and protocols with which it is related. Numerous services are not offered actively. As a result, this article is titled Artificial Immune System (AIS) Algorithm-Based Traffic Prediction, which describes how this algorithm is utilized to anticipate long-term underlying causes. Data on urban data flow are used to make predictive estimations of data sensitivity. The simulation results demonstrate that the proposed sequence achieves the same accuracy as random predictions while requiring fewer blocks than standard solutions.