A video processing and machine vision-based automatic analyzer to determine sequentially total suspended and settleable solids in wastewater

Abstract

The monitoring of total suspended (TSS) and settleable (SetS) solids in wastewater is essential to maintain the quality parameters for aquatic biota because they can transport pollutants and block light penetration. Determining them by their respective reference methods, however, is laborious, expensive, and time consuming. To overcome this, we developed a new analytical instrument called Solids in Wastewater's Machine Vision-based Automatic Analyzer (SWAMVA), which is equiped with an automatic sampler and a software for real-time digital movie capture to quantify sequentially the TSS and SetS contents in wastewater samples. The machine vision algorithm (MVA) coupled with the Red color plane (derived from color histograms in the Red-Green-Blue (RGB) system) showed the best prediction results with R2 of 0.988 and 0.964, and relative error of prediction (REP) of 6.133 and 9.115% for TSS and SetS, respectively. The constructed models were validated by Analysis of Variance (ANOVA), and the accuracy and precision of the predictions by the t- and F-tests, respectively, at a 0.05 significance level. The elliptical joint confidence region (EJCR) test confirmed the accuracy, while the coefficient of variation (CV) of 6.529 and 10.908% confirmed the good precisions, respectively. Compared with the reference method (Standard Methods For the Examination of Water and Wastewater), the proposed method reduced the analysis volume from 1.5 L to just 15 mL and the analysis time from 12 h to 24 s per sample. Therefore, SWAMVA can be considered an important alternative to the determination of TSS and SetS in wastewater as an automatic, fast, and low-cost analytical tool, following the principles of Green Chemistry and exploiting Industry 4.0 features such as intelligent processing, miniaturization, and machine vision.