Natural disasters, particularly landslides, pose significant threats to lives and infrastructure. This paper proposes an IoT-based wireless sensor network (WSN) for real-time landslide monitoring and early warning. The system integrates soil moisture, accelerometer, and vibrational sensors to monitor environmental parameters indicating slope instability. Data is processed using statistical and machine learning models to identify patterns that predict landslide risks. Results demonstrate the system’s potential to provide timely warnings, reduce damage, and save lives.