Water & Wastewater Asia July/August 2022

SINGAPORE FOCUS
EVENT-TRIGGERED PIPELINE
leak detection system
An R&D collaboration between Teredo Analytics and PUB’s
water supply network department. By Wong Liang Jie and Dr Rajat Mishra
Teredo Analytics is a deep tech start-up
incorporated under the NUS Graduate
Research Innovation Programme (GRIP). Its
co-founders are former researchers from
NUS Acoustic Research Laboratory (ARL)
and draw on their expertise in acoustic signal
processing, big data analytics, the Internet
of Things (IoT) and artificial intelligence (AI)
to develop monitoring solutions for water
pipeline networks and water plant machinery.
The developed technology was able to
detect leaks along PUB’s water pipeline
networks and has since been patented. This
technology has also been adapted to provide
continuous condition monitoring on water
plant machinery, enabling early detection of
potential machinery failure.
detection. As such, the delay in which
the authority will be alerted to a leak can
potentially exceed 20 hours and given the
leak size, the water loss and disruption to
the public can be substantial. In addition,
the authority is also faced with a high falsepositive
alarm rate from previously installed
systems where environmental acoustic
signatures are mistakenly interpreted as
pipe leaks.
The solution includes a two-fold check
based on the frequencies of the acoustic
signatures and a machine learning (ML)
framework which will reduce the number
of false-positive alerts arising from noisy
non-leak activities such as construction
work. This involves a leak-event triggered
mechanism with the ability to notify the leak
detection system and send the acoustic
signature of interest to the cloud platform
for further processing. The event-based
alert mechanism is based on a low-power
circuit that notifies the processor upon
detecting a persistent leaking acoustic
signature.
The R&D collaboration between PUB and
Teredo Analytics seeks to develop the next
generation of low-powered leak detection
system that is capable of detecting near
real-time leaks with a low false-positive
alarm rate. This is made possible with the
technological advancement in low-powered
microprocessors and an AI algorithm
residing in a cloud-based architecture that
analyses and processes a large number of
acoustic datasets collected.
System architecture of Teredo’s event-based leak detecting Listener system
Existing battery-operated leak detection
systems that are installed on the water
pipeline network are pre-configured to
be alerted at a pre-defined time to record
leak-associated data parameters such as
acoustics and pressure. Such an approach
can only alert the authority upon detecting
a leak during its pre-configured time and
is thus unable to provide real-time leak
A schematic diagram of the event-triggered leak-detecting circuit
10 WATER & WASTEWATER ASIA | JULY/AUGUST 2022