## 1 Introduction  
Inadequate sanitation and a lack of personal hygiene exacerbate the spread of infectious diseases such as typhoid, cholera, diarrhea, and amoebic dysentery [1, 2, 3]. These water-borne diseases affect one-quarter of the world's population under five [4]. An acute lack of sanitation infrastructure establishes a behavioral tendency toward open defecation, which increases the probability of intestinal worms, diarrhea, and environmental enteric dysfunctions [5]. According to UN estimates, over 5% of the world's population still defecates openly due to a lack of access to basic sanitation facilities, with the majority of this population concentrated in two regions--233 million people in Southern and Central Asia and another 197 million in Sub-Saharan Africa [6]. This situation is all the more disadvantageous for developing countries with high populations such as India. The situation deteriorates further as the population density is high due to increased exposure to fecal pathogens. On the other hand, the UN University's Centre for Water Environment and Health predicts that if all human excrement from latrines were collected and burned above 300 \({}^{\circ}\)C, up to 8.5 million tonnes of fecal ash might be generated. Additionally, this will assist in extracting nutrients from the soil and provide a source of revenue. Similarly, wastewater streams are nutrient-dense and include plant leftovers used in various agricultural applications [7; 8]. This shows unequivocally that human feces offer a unique perspective into the issues of emerging contaminants. However, increasing the number of toilets is not enough to combat water-borne diseases or achieve the Sustainable Development Goals. Improved methods of collection and treatment of human feces also play a detrimental role in creating a safe and efficient sanitation system [9; 10]. Fecal sludge contains several nutrients that may be used in various applications, and hence, there is a rise in demand for the development of treatment methods for the same [3]. Many technologies have been developed for decontaminating wastewater streams, such as ion exchange, adsorption, activated sludge, membrane separation, and advanced oxidation [11]. Adsorption is a process of sequestrating contaminants by an adsorbent, typically a highly porous substance with excellent selectivity. It is primarily produced from wastes generated from industries, agricultural fields, domestic/municipal garbage [12; 13; 14; 15]. Adsorption is also favored because it is low cost, simple to scale up, efficient on both small and big scales, and uses less energy, making it a step toward carbon neutrality. Although several isotherm models may be employed to describe adsorption processes, the Langmuir (single-layer homogeneity) and Freundlich (multilayer heterogeneity) isotherms are two of the most common ones used [16]. With artificial neural networks (ANN) emergence, a new model for adsorption has gained prominence [17; 18; 19]. Artificial neural network (ANN) is a computing technique associated with artificial intelligence, drawing similarities from the human nervous system. It can be described as a structured machine learning protocol drawing parallels to the human brain. The protocol consists of layers featuring different processors (called neurons) tasked with critical processing information for the system. These neurons form connections with each other, thereby forming a network of neurons, and are capable of yielding acute outputs of a susceptible algorithm [20]. The system largely relies on these networks to solve a problem and utilize data set similarities and relationships. As a result, rather than being preprogrammed, the system develops through experience. It also increases mobility since data interpretation methods may be modified throughout the study. The network's main aim is to complete the specific tasks assigned to it and simultaneously learn from a benchmark provided, e.g., the system can be tasked to predict TN (true negative) and TP (true positive) values.