Deep learning techniques and algorithms are emerging as a disruptive technology with the
potential to transform global economies, environments and societies. They have been …

Water distribution systems are susceptible to contamination events, which can occur due to
naturally occurring events, accidents or even malicious attacks. When a contamination event …

Contamination events in water distribution networks (WDNs) can have a huge impact on
water supply and public health; increasingly, online water quality sensors are deployed for …

This study presents a new stacking ensemble model for contamination event detection using
multiple water quality parameters. The stacking model consists of a number of machine …

Contamination events in water distribution networks (WDN) pose significant threats to water
supply and public health. Rapid and accurate contamination source identification (CSI) can …

Drinking water is essential to public health and socioeconomic growth. Therefore, assessing
and ensuring drinking water supply is a critical task in modern society. Conventional …

Monitoring water quality in reservoirs is essential for the maintenance of aquatic ecosystems
and socioeconomic services. In this scenario, the observation of abrupt elevations of …

As the final and crucial link in delivering clean water to consumers, the water distribution
system faces the risk of water quality deterioration. Conventional water quality parameter …

Anomaly detection techniques in the Industrial Internet of Things (IIoT) are driving traditional
industries towards an unprecedented level of efficiency, productivity and performance. They …

Researchers have developed novel approaches and algorithms to aid in the planning,
design, and administration of water distribution systems (WDS) since the 1960s. While early …