Household greywater treatment using phytoremediation technology and CapsNet model

Aims and Background In recent decades, recycling of wastewater has received increasing attention among researchers, because it can satisfy the proliferating demand for groundwater and reduce water shortages in developed and developing countries. Methods A deep learning technique, CapsNet, was developed to predict the optimal plant for household greywater treatment. Then, a greywater treatment system was developed by utilizing phytoremediation technology with horizontal flow wetland construction to utilize the final treated water for organic gardening. Results Evaluation parameters like color, odor, temperature, pH, electrical conductivity, free residual chlorine, chloride, sulfate, Salmonella spp, Total Dissolved Solids (TDS), Total Suspended Solids (TSS), oil and grease, sulfide, Chemical Oxygen Demand (COD), E. coli, Biochemical Oxygen Demand (BOD), and Nitrate Nitrogen were used to analyze the performance of the greywater treatment system. Conclusion The experimental outcomes showed that Typha angustifolia achieved an effective outcome in greywater treatment compared with other plants, where most of the parameter values of the effluent were low compared with those of the influent. Most of the parameters like pH and TDS were higher than those of the groundwater aquifers, but fell within the world health organization safety limits.