In this work, we investigate the finite-time average coherence challenge within networked autonomous entities, formulating a fixed-time synchronization scheme leveraging a dynamic event triggering mechanism. The proposed synchronization framework accelerates collective alignment in distributed agent networks, concurrently optimizing resource utilization. By implementing adaptive activation thresholds, the event-driven architecture effectively prolongs dormant phases separating sequential actuation cycles. Embedded state-tracking parameters autonomously suppress redundant operations, achieving reduction in power dissipation across heterogeneous agent clusters. Experimental validation demonstrates the algorithm’s functional robustness.