Digital Image Processing and Analysis for Activated Sludge Wastewater Treatment

Abstract

Activated sludge system is generally used in wastewater treatment plants for processing domestic influent. Conventionally the activated sludge wastewater treatment is monitored by measuring physico-chemical parameters like total suspended solids (TSSol), sludge volume index (SVI) and chemical oxygen demand (COD) etc. For the measurement, tests are conducted in the laboratory, which take many hours to give the final measurement. Digital image processing and analysis offers a better alternative not only to monitor and characterize the current state of activated sludge but also to predict the future state. The characterization by image processing and analysis is done by correlating the time evolution of parameters extracted by image analysis of floc and filaments with the physico-chemical parameters. This chapter briefly reviews the activated sludge wastewater treatment; and, procedures of image acquisition, preprocessing, segmentation and analysis in the specific context of activated sludge wastewater treatment. In the latter part additional procedures like z-stacking, image stitching are introduced for wastewater image preprocessing, which are not previously used in the context of activated sludge. Different preprocessing and segmentation techniques are proposed, along with the survey of imaging procedures reported in the literature. Finally the image analysis based morphological parameters and correlation of the parameters with regard to monitoring and prediction of activated sludge are discussed. Hence it is observed that image analysis can play a very useful role in the monitoring of activated sludge wastewater treatment plants.

Characterization of Filamentous Flocs to Predict Sedimentation Parameters Using Image Analysis

“…Image analysis is proposed as a tool to analyze and predict this phenomenon, a method that has a wide potential for the control of this type of process [8][9][10][11]. In order to compare and improve the image analysis system and find the best method of classifying data, various works carried out on water treatments are taken as references [12][13][14][15][16], which show the advantages of using an autonomous control system to increase water savings. The adoption of a mathematical model to predict the behavior of the settling velocity is a complex problem as already mentioned, so it is usual to resort to experimental laboratory processes where the sludge of the treatment plant is used to obtain more accurate velocity values in the plant.…”

Determinação da demanda química de oxigênio (DQO) em efluentes a partir da aquisição de imagens digitais utilizando smartphone

“…Protótipo de colorímetro por aquisição de imagens para determinar a concentração de fósforo em águas naturais já foram construídos, reduzindo o tempo de análise e facilitando o transporte do equipamento visto seu tamanho [16] . Assim como a determinação de nitrito em amostras utilizando reagentes de Griess [17] e o monitoramento e caracterização do estado atual do lodo ativado [18] .…”

Segmentation Approach Towards Phase-Contrast Microscopic Images of Activated Sludge to Monitor the Wastewater Treatment

“…The performance of the process is conventionally monitored by physico-chemical procedures that are time-consuming, laborious, and have associated environmental hazards (Boztoprak et al, 2015; Mesquita et al, 2016). Image processing and analysis is a clean, time-efficient, and semi-automated alternative to monitor AS in a wastewater treatment plant (Mesquita et al, 2013; Khan et al, 2015 a , 2015 b ). The performance of the AS process depends on the settling ability of flocs, and the presence of filamentous bacteria, in the secondary clarifier of the wastewater treatment plant.…”