IoT-Controlled Upflow Filtration Achieves High Removal of Fine Particles and Phosphorus in Stormwater

Urban stormwater runoff, particularly during first-flush events, carries high loads of fine suspended solids and phosphorus that are difficult to remove with conventional best management practices (BMPs). This study developed and evaluated a laboratory-scale high-efficiency up-flow filtration system with Internet of Things (IoT)-based autonomous control. The system employed 20 mm fiber-ball media in a modular dual-stage up-flow configuration with optimized coagulant dosing to target fine particles (<3 μm) and total phosphorus (TP). Real-time turbidity and pressure monitoring via sensor networks connected to a microcontroller enabled wireless data logging and automated backwash initiation when thresholds were exceeded. Under manual operation, the two-stage filter achieved removals of 96.6% turbidity, 98.8% suspended solids (SS), and 85.6% TP while maintaining head loss below 10 cm. In IoT-controlled single-stage runs with highly polluted influent (turbidity ~400 NTU, SS > 1000 mg/L, TP ~1.6 mg/L), the system maintained >90% SS and ~58% TP removal with stable head loss (~8 cm) and no manual intervention. Turbidity correlated strongly with SS (R2 ≈ 0.94) and TP (R2 ≈ 0.87), validating its use as a surrogate control parameter. Compared with conventional BMPs, the developed filter demonstrated superior solids capture, competitive phosphorus removal, and the novel capability of real-time autonomous operation, providing proof-of-concept for next-generation smart BMPs capable of meeting regulatory standards while reducing maintenance.