Research on Location Privacy in Wireless Sensor Networks (WSNs) aims to protect the geographical information of sensor nodes and data sources from adversaries that attempt to trace the origin or location of transmitted data. Since WSNs are often deployed in sensitive environments like military, healthcare, and habitat monitoring, maintaining location privacy is critical for network security. Recent approaches incorporate differential privacy, obfuscation techniques, random routing, and game-theoretic models to conceal node positions and communication patterns without significantly increasing energy consumption or latency. Machine learning-based adaptive privacy mechanisms and blockchain-assisted frameworks are also being explored to ensure stronger anonymity and resistance against traffic analysis attacks. Overall, location privacy preservation has become an essential research focus to balance data confidentiality, network performance, and energy efficiency in modern WSN applications.