Recent research on context-aware routing in wireless sensor networks (WSNs) focuses on utilizing environmental, temporal, and node-specific contextual information to enhance routing efficiency, reliability, and adaptability. Context-aware protocols dynamically adjust routing decisions based on factors such as node energy levels, link quality, mobility, and data priority, enabling more intelligent and adaptive communication paths. Modern studies integrate trust management, fuzzy logic, and machine learning models to predict network conditions and select optimal routes under varying contexts. These approaches significantly improve energy utilization, data delivery ratio, and network resilience, especially in heterogeneous and application-specific WSN deployments like smart agriculture, healthcare monitoring, and industrial IoT systems.