Research on Opportunistic Routing in Wireless Sensor Networks (WSNs) focuses on improving data delivery reliability and energy efficiency by dynamically selecting relay nodes based on real-time network conditions instead of predetermined paths. Unlike traditional routing, opportunistic routing exploits the broadcast nature of wireless communication, allowing multiple candidate nodes to overhear and cooperate in forwarding packets, thereby increasing transmission success rates in unreliable environments. Recent studies integrate trust-based, machine learning, and reinforcement learning approaches to intelligently choose the best forwarding nodes while minimizing energy consumption and delay. Additionally, energy-aware and QoS-driven opportunistic protocols have been developed to balance load, enhance throughput, and adapt to mobility or varying link quality. Overall, opportunistic routing enhances resilience, reduces retransmissions, and improves overall network performance, making it a vital solution for dynamic and large-scale WSN applications.