Chapter 1 - Smart sensing technologies for wastewater treatment plants

Abstract

The wastewater treatment plants performance is a function of various factors including wastewater quality, management conditions of the treatment plant, and environmental issues. Disposal of wastewater with acceptable quality characteristics to a variety of receiving sources is one of the environmental problems that today's societies face. In addition to transmitting microbial and chemical pathogens to humans, wastewater release destroys many aquatic species in rivers, lakes, and oceans. Due to its inherent and nonlinear characteristics, modeling a municipal sewage refinery is complex and difficult. Due to the increasing concerns about the environmental effects of refineries due to poor operation, fluctuations of process variables, and problems of online analyzers, artificial process control algorithms such as artificial neural networks have attracted a lot of attention due to increasing intelligence. An artificial intelligence network is a set of neurons that are located in different layers, forming a special architecture based on the connection between neurons. So that, the neuron is a nonlinear mathematical unit, and as a result, a neural network will be a complex and nonlinear system. This chapter discusses the literature to conduct a large-scale bibliometric analysis of traits inside the application of artificial intelligence generation to wastewater treatment. In addition, the use of marine sensors for simultaneous collection of relevant environmental data in parallel with the acquisition of visual data in error detection and detection, online estimation, and analysis of multivariate models will be investigated.