Leveraging Transfer Learning in LSTM Neural Networks for Data-Efficient Burst Detection in Water Distribution Systems

Researchers and engineers employ machine learning (ML) tools to detect pipe bursts and prevent significant non-revenue water losses in water distribution systems (WDS). Nonetheless, many approaches developed so far consider a fixed number of sensors, which requires the ML model redevelopment and collection of sufficient data with the new...

Evidence of regional sea-level rise acceleration for the North Sea

Global mean sea-level rise (SLR) has accelerated since 1900 from less than 2 mm yr-1 during most of the century to more than 3 mm yr-1 since 1993. Decision-makers in coastal countries, however, require information on SLR at the regional scale, where detection of an acceleration in SLR is difficult, because the long-term sea-level signal is...

A new method to detect changes in displacement rates of slow-moving landslides using InSAR time series

Slow-moving landslides move downslope at velocities that range from mm year⁻¹ to m year⁻¹. Such deformations can be measured using satellite-based synthetic aperture radar interferometry (InSAR). We developed a new method to systematically detect and quantify accelerations and decelerations of slowly deforming areas...

Real-time Face and Landmark Localization for Eyeblink-Response Detection: A heterogenous CPU-GPU approach

Pavlovian eyeblink conditioning is a powerful experiment used in the field of neuroscience to measure multiple aspects of how we learn in our daily life. To track the movement of the eyelid during an experiment, researchers traditionally made use of potentiometers or electromyography (EMG). More recently, the use of computer vision and image...

Optimised control and pipe burst detection by water demand forecasting

Water demand forecasting The total water demand in an area is the sum of the water demands of all individual domestic and industrial consumers in that area. These consumers behave in repetitive daily, weekly and annual patterns, and the same repetitive patterns can be observed in the drinking water demand. The observations of the water demand...

Detecting Pipe Bursts Using Heuristic and CUSUM Methods

Pipe bursts in a drinking water distribution system lead to water losses, interruption of supply, and damage to streets and houses due to the uncontrolled water flow. To minimize the negative consequences of pipe bursts, an early detection is necessary. This paper describes a heuristic burst detection method, which continuously compares...

Detecting pipe bursts by monitoring water demand

An algorithm which compares measured and predicted water demands to detect pipe bursts was developed and tested on three data sets of water demand and reported pipe bursts of three years. The algorithm proved to be able to detect bursts where the water loss exceeds 30% of the average water demand in the area. The accuracy depends on the...

Monitoring water supply systems for anomaly detection and response

Water supply systems are vulnerable to damage caused by unintended or intended human actions, or due to aging of the system. In order to minimize the damages and the inconvenience for the customers, a software tool was developed to detect anomalies at an early stage, and to support the responsible staff in taking the right decisions to restore...