Wireless Sensor Networks (WSNs) have emerged as an essential technology for monitoring and data collection in applications such as environmental surveillance, healthcare, industrial automation, agriculture, and smart cities. Since sensor nodes operate with limited battery resources and are often deployed in inaccessible environments, energy efficiency remains one of the most critical challenges in WSN design. Routing protocols play a significant role in determining network performance because communication consumes a major portion of node energy. This paper presents a comprehensive study of energy-efficient routing techniques in Wireless Sensor Networks. Various routing protocols, including flat, hierarchical, location-based, hybrid, multipath, query-based, negotiation-based, and Quality of Service (QoS)-based approaches, are discussed and theoretically classified. The study also reviews prominent protocols such as LEACH, PEGASIS, TEEN, HEED, DEEC, GEAR, and SPIN, highlighting their characteristics, advantages, limitations, and energy conservation capabilities. Furthermore, recent advancements in Artificial Intelligence, Machine Learning, Fuzzy Logic, Particle Swarm Optimization, and Ant Colony Optimization-based routing techniques are examined. Comparative analysis indicates that intelligent and adaptive routing approaches provide superior energy efficiency, scalability, load balancing, and network lifetime, making them promising solutions for future WSN and Internet of Things (IoT) applications.

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