The significance of data packet transmission reliability is increasing as Wireless Sensor Network (WSN) is becoming more extensively utilized. It is essential that the protocols for routing the data packets are reliable and secure is accurate data packet delivery possible. The current cryptographic algorithms may not be used for WSN security due to WSN restrictions. In a while, the Trust Aware Energy Efficient Routing (TAEER) mechanism has developed as a benefit for successful packet transmission with higher security and may give effect with fewer resources. The TAEER system, however, suffers congestion due to a large demand for resources during the active period and a delay between the speed of data processing and transmission and the speed of incoming traffic. By causing buffer overflow, packet loss, increased latency, excessive energy consumption, or, worse still, the failure of the overall system, this may interfere with entire network. A Priority-based Congestion Trust Aware Energy Efficient Routing Algorithm (PCTA-EERA) is presented in this research using an improved fuzzy based trust management system as well as the Chaotic Weight Dragonfly Algorithm (CWDA). The data transmission has been classified into regular, on-demand, and emergency data for the prioritised routing process. Identifying the nearest nodes is done by neighbour discovery. CWDA serves as the Cluster Head in clustering (CH). For the objective of selecting a CH, node factors like node-to-base station distance, path loss, node weight, queue length, residual energy, link reliability, and node reachability have been taken into consideration. Malicious nodes have been detected through improved fuzzy based trust management in order to enhance the security. For successful packet transmission, Time Division Multiple Access (TDMA) scheduling had been being adopted. In terms of Packet Delivery Ratio (PDR), Energy Consumption, End to End Delay (E2E), Network Lifetime (NL), Transmission Rate (TR), and Average Remaining Round (ARR), the experimental findings demonstrate that the proposed system outperforms the existing system.