The document describes an event recognition system (ERS) developed by Exeter University and implemented by United Utilities to detect leaks and bursts in water distribution systems. The ERS analyzes near real-time pressure and flow sensor data using statistical and machine learning techniques to automatically detect events and their approximate locations. Testing showed the ERS can reliably detect events within 30 minutes with few false alarms and identify burst precursors. United Utilities has further developed the ERS and uses it operationally across their network, saving over 1 million pounds per year.

1. Event Recognition System for
Smart Monitoring of Water
Distribution Systems
Michele Romano
Operational Technology Analytics Team
United Utilities

2. Outline
• United Utilities (UU) Intro
• Leaks & Burst Problem
• Exeter Event Recognition System (ERS)
 Methodology
 Capabilities
• UU ERS
• Wider Applicability
• Summary
Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano

3. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
United Utilities (UU)
• Main licensed water and
wastewater company for the
North West of England
• Supplies almost 2,000 ML/day
of water to 7 million people
through a network of 42,000
Km of water mains

4. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
UU Vision & Goals

5. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
Water Network Operating Model
No longer using the customers as the eyes and ears of the network but
adopting a preventative and proactive approach to network operation
and management

6. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
Leaks & Bursts Problem
UU loses 452 ML/day of treated and frequently pumped water
through leaks and bursts
• Waste of resources
• Financial loss
• Potential health risk
• Negative PR
Many leak detection methods exist but none ideal

7. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
Hydraulic Data Availability
• Larger number of flow and pressure devices to be deployed
• Large amounts of data to be collected
However, the volume and complexity
of the data received often exceed
the human capability to analyse,
interpret and extract useful
information
The latest developments in hydraulic sensor technology and on-line data acquisition systems have
enabled:

8. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
Exeter University ERS
Fully automated, data-driven and self-learning system for the
timely and reliable detection and location of bursts/other network
events as they occur in a District Metered Area (DMA) by using
near real-time (e.g., 15 min) pressure and flow data

9. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
Exeter ERS Methodology
Evidence Analysis
•Bayesian Networks
•Geostatistical techniques
Flow Sensor
Pressure
Sensor
Signal Analysis
•Wavelets
•Artificial Neural Network
•Evolutionary Algorithms
•Statistical Process Control
•Bayesian Network
Signal Analysis
•….
•….
(1) Raise detection alarms
(2) Determine the
approximate location of
an event within the DMA
REFERENCES:
Romano, M., Kapelan, Z., and Savić, D.
(2014). “Automated Detection of Pipe Bursts
and Other Events in Water Distribution
Systems”. Journal of Water Resources
Planning and Management, 140 (4), 457–
467.
Romano, M., Kapelan, Z., and Savić, D.
(2014). “Evolutionary Algorithm and
Expectation Maximisation Strategies for
Improved Detection of Pipe Bursts and
Other Events in Water Distribution Systems”.
Journal of Water Resources Planning and
Management, 140 (5), 572–584.
Romano, M., Kapelan, Z., and Savić, D.
(2013). “Geostatistical Techniques for
Approximate Location of Pipe Burst Events
in Water Distribution Systems” Journal of
Hydroinformatics, 15 (3), 634-651.

10. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
Exeter ERS Capabilities
• Exeter ERS tested and verified on a number of UU DMAs with real-life and engineered (i.e., simulated by
opening fire hydrants) events
• The results obtained have shown its ability to:
– Successfully detect events in a timely (within 30 minutes) and reliable manner (with a very low false alarms rate –
i.e., typically below 10%)
– Successfully determine the approximate location of bursts within a DMA
– Perform ‘predictive’ event recognition - e.g., to identify burst precursor features (issues that are not yet having a
customer impact) thereby enabling their repair before they result in more costly pipe bursts
– Perform ‘proactive’ event recognition - e.g., to detect a burst event occurrence before the customers become
aware of a problem with their water supply

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Alarm raised following the failure of a
Pressure Management Valve (PMV)
The ERS alarm could
have been used to
schedule a proactive
PMV maintenance
intervention and
prevent the burst(s)
ERS alarm 6th of February @ 12:15
1st burst event on the 7th February
1st Customer Contact 7th February @ 12:08
Repair 7th February @ 16:00
2nd burst event on the 12th February
Predictive ER - Example

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22 ottobre 2015, Palazzo Turati Milano
Proactive ER - Example
Alarm raised following a pipe burst
event
• 53 properties affected
• 11 Customer Contacts (CCs)
received – 1st CC received more
than 6 hours after the ERS alarm
The ERS alarm
could have been
used to schedule
a main repair
intervention and
restore supplies
sooner

13. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
UU ERS
• Cutting-edge and award winning/appealing system that include further developments
to the Exeter ERS to enable effective integrated event management (e.g., alarm ranking,
likely root-cause identification, handling alarms from cascading DMAs, etc.)
• Built on a strategic platform called OsiSoft PI, which will allow it to grow in line with the
Business
• Local enterprise solution using existing applications and locally held data
• Lower total cost of ownership than third-party applications (Capital and O&M costs)
• Used operationally companywide for analysing data from more than 7000 loggers since
April 2015
• Improved service to UU’s 7 Million customers with 1.2 Million Pounds per year
operational cost savings

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ERS Methodology Wider Applicability
Current Trials:
– Water networks for water quality monitoring and (un)intentional contamination ER
– Water networks for decision support and event management (i.e., integration of ER with GIS, up-to-
date network connectivity maps, valves status information, customer contacts information, work
management system information, dynamic network models, etc.)
– Water Treatment Works (WTWs) for water quality monitoring and ER
Future Applications:
– Wastewater (e.g., real-time detection of blockages / collapses)
– Customers

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22 ottobre 2015, Palazzo Turati Milano
Summary
• Regulatory pressure is increasing, encouraging UU to adopt Smart water technologies and methods for
innovative network operation and management
• Exeter ERS has proven that the near-real time pressure and flow measurements collected by modern
SCADA systems can be successfully used for detecting and locating pipe bursts and other similar network
events both quickly and economically
• ERS technology proven to be customisable to UU’s needs and has resulted in an in-house, low-cost
solution that is currently used operationally companywide, contributing towards achieving UU’s strategy
and vision, benefitting UU’s customers and yielding substantial operational cost savings
• On-going investment and R&D programme – e.g., transfer to wastewater part of the business; water
quality/quantity

16. Smart Water in the city of the future
22 ottobre 2015, Palazzo Turati Milano
Thank you for your attention!
Questions?
Michele Romano
EICA Engineer – Operational Technology
Michele.Romano@uuplc.co.uk
+44(0)1925 731147
+44(0)7534 547863