Current respiratory pathogen surveillance is largely based on case reporting, sentinel surveillance, and environmental sampling. This study developed an autonomous pathogen detection system (APDS) integrating real-time bioaerosol sensing, intelligent triggering, aerosol collection, nucleic acid extraction, real-time PCR, and automated data reporting for respiratory pathogen surveillance. System performance was evaluated in a 20 m³ aerosol chamber and through 52 weeks of continuous monitoring in a hospital outpatient hall in Beijing. Laboratory experiments showed that the developed platform enables the detection of airborne influenza A virus at concentrations as low as 3.75 × 10⁴ 50% tissue culture infectious dose/m³ and can detect airborne Pseudomonas aeruginosa at concentrations as low as 1.80 × 10⁴ copies/m³. The platform can detect low concentrations of airborne pathogen nucleic acids that are undetectable by surface sampling. During field monitoring, APDS autonomously triggered 381 tests and recorded 46 pathogen-positive detections. Respiratory syncytial virus showed significant correlations when APDS signals preceded national surveillance data by 1–3 weeks, with the strongest correlation at a 3-week lead (ρ = 0.487). Given the spatial mismatch between single-site APDS monitoring and national surveillance data, this association should be considered exploratory. These findings demonstrate the feasibility of APDS for long-term automated aerosol surveillance and suggest its potential as a complementary tool for respiratory pathogen monitoring.