Water Utilities Deploy 34,000 Sensors and €8 Million Robots to Fight Sewer Fatbergs
Updated
Updated · BBC.com · May 12
Water Utilities Deploy 34,000 Sensors and €8 Million Robots to Fight Sewer Fatbergs
3 articles · Updated · BBC.com · May 12
Southern Water has installed about 34,000 sewer sensors and uses machine-learning models to flag abnormal water levels, helping crews catch fatberg buildups before they harden into major blockages.
The push targets a costly, fast-growing problem: UK utilities clear about 300,000 fat, oil and grease accumulations a year, while New York spends roughly $18.8 million annually on grease-related sewer blockages.
Southern Water says AI has already helped clear 700 blockages this year; blocked or overwhelmed sewers still caused more than 15,500 sewage spills in 2025, though that was 47% lower than in 2024.
Robotics is the next step. An €8 million EU-backed project is developing autonomous sewer robots with cameras, LiDAR and acoustic sensors that could inspect pipes and eventually grasp and remove blockages.
The technology aims to reduce sewage flooding and pollution while keeping workers out of hazardous tunnels filled with hydrogen sulphide, methane, bacteria and other sewer contaminants.
As AI predicts sewer blockages, will cities start fining the households and businesses found to be responsible?
Could our disgusting fatbergs be mined from sewers and converted into a valuable source of green biofuel?
What everyday products are secretly fueling the creation of these concrete-hard sewer monsters?
From Fatberg Crisis to 47% Fewer Spills: The Impact of AI and Robotics on UK Sewers (2025-2026)
Overview
Between 2025 and 2026, water companies made major progress in fighting fatbergs by shifting from reactive methods to a proactive, data-driven approach. Southern Water led this change by installing about 34,000 sensors on manhole covers across its sewer network. These sensors use radar to measure water flow and depth in real time. The data is sent to an AI system, which combines it with weather information to predict normal water levels. When unusual levels are detected, the system triggers alerts, allowing teams to quickly address blockages before they become serious pollution problems.