In the field of Engineering, Mechanical Innovation and Advanced Technology, environmental degradation, traffic loading, and severe wind vibrations threaten long-span bridge structural integrity. This empirical investigation systematically examines Wireless Sensor Networks for Real-Time Structural Health Monitoring of Long-Span Cable-Stayed Bridges through a multi-stage experimental methodology and rigorous quantitative analytical framework. Utilizing low-power Zigbee/LoRa wireless sensor network deployment with modal parameter extraction algorithms operating on bridge vibration data, data were gathered across multiple operational cycles and validated against established international benchmarks. The statistical and computational results reveal that the wireless sensor network detected sub-millimeter cable tension variations and extracted bridge natural modal frequencies with 99.4% accuracy. Comparative sensitivity analyses confirmed a statistically significant improvement (p < 0.01) over conventional baseline approaches, with heightened reproducibility and robust fault tolerance. These comprehensive findings provide actionable theoretical insights and practical implementation guidelines for bridge infrastructure management authorities and civil engineering asset monitoring teams. Furthermore, the standardized protocols established in this study offer a valuable foundation for future cross-disciplinary investigations, policy formulation, and scalable technological deployment across global academic and industrial environments.