FoulGuardAI offers an AI-driven system that detects biofouling in water‑treatment facilities, alerting operators before performance drops. By continuously analyzing sensor and imaging data, the platform identifies early-stage fouling patterns, enabling timely cleaning and reducing downtime and maintenance costs.
Funding
Funding not disclosed
Founders
Product
Problem
Water treatment facilities often experience biofouling on membranes and infrastructure, which reduces system efficiency, increases energy consumption, and leads to unplanned downtime for cleaning and maintenance.
Solution
FoulGuardAI offers an AI-driven monitoring platform that continuously analyzes visual data from existing inspection cameras to detect early signs of microbial growth on membranes and equipment. The system applies computer‑vision models trained on fouling patterns to generate real‑time alerts and trend analytics. By integrating with the plant’s SCADA system, operators receive actionable notifications that enable scheduled, targeted cleaning, minimizing unnecessary shutdowns and extending equipment lifespan.
Target Audience
Primary customers are operators and maintenance teams at municipal and industrial water treatment plants that rely on membrane filtration and require proactive fouling management.
Features
- Real‑time biofouling detection using deep‑learning computer‑vision algorithms on live camera feeds
- Automated alert generation with severity scoring and recommended cleaning actions
- Seamless integration with SCADA and PLC environments via standard OPC-UA or MQTT interfaces
- Historical analytics dashboard showing fouling progression, cleaning effectiveness, and equipment health metrics
- Configurable detection thresholds and customizable reporting for different membrane types and process conditions