Recent research in energy-efficient routing protocols for wireless sensor networks focuses on developing intelligent, adaptive routing mechanisms that minimize power consumption while maintaining reliable data transmission. Modern studies integrate optimization algorithms, machine learning, and clustering strategies to enhance routing decisions based on residual energy, link quality, and node density. Researchers are emphasizing dynamic route selection and multipath strategies that balance energy load among nodes, thereby prolonging network lifetime and improving scalability. These approaches demonstrate the growing importance of context-aware and self-organizing routing techniques for efficient energy utilization in large-scale, heterogeneous sensor environments.