Southern Water has partnered with specialist expertise firm Samotics to deploy its SAM4 sensible situation monitoring system at websites throughout southern England. The bogus intelligence (AI) powered expertise makes use of electrical signature evaluation (ESA) to assist predict when gear in each wastewater and clear water networks is more likely to fail, decreasing the chance of service interruptions and environmental air pollution. (Phrases: Samotics)
The £7 million, six-year framework settlement, signed in September 2025, follows a profitable one-year onsite trial that demonstrated SAM4’s effectiveness. Through the trial, Samotics’ expertise detected 63 gear failures on submersible sewage pumps and different key pumping belongings throughout the sewage community and remedy works. This included blockages, air locks, and mechanical faults – serving to keep away from an estimated £5 million in potential gear harm and penalties.
At the moment, 1,458 vital Southern Water belongings are being monitored by Samotics’ expertise on round 600 websites, and the quantity is scheduled to extend in 2026.
John Penicud, managing director for wastewater at Southern Water stated, “Unplanned failures of vital gear can result in a unfavorable influence on our clients and the surroundings, and end in elevated operational prices. Figuring out points early is vital to profitable proactive upkeep.”
Tom Swain, Head of UK & Eire at Samotics stated, “We’re completely delighted to enter this long-term partnership with Southern Water, who proceed to steer the business in utilizing superior applied sciences to watch gear and stop asset failure. This builds on our presence within the UK water sector and our sturdy observe report in driving operational and upkeep efficiencies.
“This strategic initiative represents a significant step ahead in modernising water infrastructure. It captures insights, drives effectivity, improves asset efficiency and resilience, and helps environmental sustainability.”
Samotics’ SAM4 system makes use of ESA to watch industrial gear by analysing present and voltage alerts in real-time, whereas AI interprets deviations from regular operation and classifies them into particular fault varieties. This implies points reminiscent of misaligned parts, bearing put on, and pump blockages are rapidly recognized, even on hard-to-reach belongings, serving to predict and stop gear failure.
Water utility employees can handle alerts remotely on the SAM4 dashboard, deploying crews to prioritised websites and sustaining computerized information of belongings, incidents and actions. By supporting these detections with human-in-the-loop validation, the system is confirmed to ship a 97% accuracy fee, with fewer than 1% false positives.
