The anticipated integration of 6G technology within the telecommunications sector is poised to significantly enhance communication capabilities in the forthcoming years. The proliferation of 6G within Etisalat's infrastructure is expected to concurrently drive the expansion of the Internet of Things (IoT), facilitating its operation across a diverse array of mobile and stationary devices. Within the IoT domain, particularly under the 6G framework, certain applications necessitate real-time operation and thus warrant prioritization over others in terms of communication and data transmission. The strategic clustering of users, based on assigned weight factors, can bolster the prioritization process, thereby optimizing the efficiency of real-time applications. This paper delineates methodologies for expediting user connectivity—termed 'real-time'—and delineates them from non-time-critical applications. The implementation of Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is proposed as a viable strategy for clustering IoT devices, thereby managing the increased volume of smaller, more granular data packets characteristic of 6G networks. Utilizing DBSCAN clustering facilitates the preemptive identification of potential user congestion and traffic, enabling the deployment of the outlined strategies to mitigate service degradation and maintain data transfer rates. This research explores the formulation of a prioritized scheduling system for requests, wherein, as per the DBSCAN algorithm, real-time applications are accorded elevated execution precedence.