Topological analysis of IoT systems using uniform neutrosophic graphs

This paper presents the idea of uniform neutrosophic topological indices, which are used to characterize the structural dynamics of the graphs in an uncertain environment. Although traditional fuzzy graph indices are effective in dealing with mild uncertainty, these indices fail to perform when the indeterminacy is critical. Neutrosophic topological indices, however, are more flexible and detailed, and, therefore, can be applied in situations where ambiguity and lack of information prevail. These indices have been computed using our approach by modifying labeling strategies on crisp graphs to the neutrosophic ones, instead of relying solely on the degrees of vertices or the weights of edges. To prove the given methodology, we developed a MATLAB algorithm, which shows the neutrosophic labeling in an Internet of Things(IoT) system. An example is provided to demonstrate that it is possible to construct uniform neutrosophic graphs, calculate the topological indices of these graphs, and discuss the obtained results with the aid of graphical plots. Its results emphasize the usefulness of neutrosophic indices in modeling uncertain and dynamic IoT-based systems, providing new insights into network analysis and intelligent decision-making.