This study was carried out to explore how sensors can be applied to monitor and predict microbial succession in anaerobic baffled reactors (ABRs) that treat high‑strength agricultural wastewater. A laboratory‑scale ABR equipped with pH sensors, oxidation–reduction potential (ORP) sensors, ion‑selective electrodes, and dissolved oxygen sensors was operated through four phases: baseline, nitrogen loading, wastewater introduction, and recovery. Sensor data showed that the nitrogen removal rates of the ABR increased from 90.2% (NH4+-N) and 99.8% (NO2−-N) at moderate loading to 96.1 and 100% under peak loading (0.289 kg/m3·d). For organic material introduction, removal rates decreased significantly [73.4% of NH4+-N, 66.1% of NO2−‑N, and 60.3% of chemical oxygen demand (COD)], coinciding with negative ORP changes and NO2− accumulation. Recovery was captured in real time, with efficiencies increased to 94.2, 100, and 94.1% for NH4+‑N, NO2−-N, and COD, respectively. Ribosomal RNA sequencing results showed microbial changes. Operational taxonomic unit richness decreased to 31159 in the wastewater introduction phase but increased to 38564 in the recovery phase. The thriving of Candidatus Kuenenia was suppressed and replaced by heterotrophic Limnobacter. The correlation between sensor data and microbial diversity indices showed that sensors can be used as proxies for ecological transitions. The results of this study serve as a reference for the sensor‑data-based diagnostics and prediction of microbial diversity changes, enabling bioreactors to achieve resilient, automated nitrogen removal under variable organic shocks.