Deep learning in wastewater treatment: a critical review.

Modeling wastewater processes supports tasks such as process prediction, soft sensing, data analysis and computer assisted design of wastewater systems. Wastewater treatment processes are large, complex processes, with multiple controlling mechanisms, a high degree of disturbance variability and non-linear (generally stable) behavior with multiple internal recycle loops. Semi-mechanistic biochemical models currently dominate research and application, with data-driven deep learning models emerging as an alternative and supplementary approach.

A Privacy-Preserving Framework Using Homomorphic Encryption for Smart Metering Systems.

Smart metering systems (SMSs) have been widely used by industrial users and residential customers for purposes such as real-time tracking, outage notification, quality monitoring, load forecasting, etc. However, the consumption data it generates can violate customers' privacy through absence detection or behavior recognition. Homomorphic encryption (HE) has emerged as one of the most promising methods to protect data privacy based on its security guarantees and computability over encrypted data.

Sweating the assets - The role of instrumentation, control and automation in urban water systems.

Instrumentation, control and automation (ICA) are currently applied throughout the urban water system at water treatment plants, in water distribution networks, in sewer networks, and at wastewater treatment plants. However, researchers and practitioners specialising in respective urban water sub-systems do not frequently interact, and in most cases to date the application of ICA has been achieved in silo. Here, we review start-of-the-art ICA throughout these sub-systems, and discuss the benefits achieved in terms of performance improvement, cost reduction, and more importantly, the enhanced capacity of the existing infrastructure to cope with increased service demand caused by population growth and continued urbanisation.