The concept of the Internet of Things (IoT) is an innovation paradigm that suggests linking physical devices together to share data and work toward a common goal. Nodes in an IoT network are anticipated to communicate with one another and with third-party Internet services. However, not all network nodes have direct Internet access due to high deployment costs. As a result, additional network nodes should be using Internet-connected nodes as gateways to transmit data to online services. Due to its central role in establishing connections between nodes in a network and distributing data packets, routing protocols have emerged as a significant challenge in IoT use cases. The work of routing is complicated in mobile IoT scenarios due to the topology changes brought on by the mobility of nodes. To better handle the mobile nature of the devices, existing Iot routing solutions typically exhibit severe constraints and poor performance in such cases. This study proposes an improvement to the existing protocols; the Cluster Formation Protocol with Neuro Fuzzy Rules, in light of the fact that main routing techniques for low-power network are unable to achieve adequate performance in the shown IoT context. The energy efficiency of the routing process in WSN can be improved with the help of cluster based routing thanks to the proposed efficient routing algorithms. In addition, the efficiency of clustering & cluster based routing protocols can be enhanced by employing intelligent approaches like fuzzy rules, temporal constraints, and categorization via deep learning. Therefore, the safe transfer of data packets from of the source point to the sink node necessitates careful consideration in the development of cluster dependent routing algorithms. The cluster dependent routing method presented is developed, evaluated with respect to a number of criteria, and shown to be effective.