Global Journal of Human Social Science, H: Interdisciplinary, Volume 23 Issue 5

© 2023 Global Journals Volume XXIII Issue V Version I Global Journal of Human Social Science - Year 2023 ( ) H 15 thermotolerances), pH, biochemical oxygen demand (BOD), total phosphorus, nitrate (total nitrogen), turbidity, solids (Total residuals) and temperature). With this, the quality curves and relative weights are determined, attributing a degree of quality referring to the values of the analyzed variables. The National Water Agency (ANA, 2022) describes the calculation of the WQI according to the following equation: Where: WQI = Water Quality Index is a number between 0 and 100. Qi = quality of the ith parameter. It is a number between 0 and 100, obtained from the respective quality graph, as a function of its concentration or measurement (analysis result). wi = weight corresponding to the ith parameter fixed according to its importance for the global conformation of quality, that is, a number between 0 and 1, so that: Where: n is the number of parameters entering into the calculation of the WQI. Fernandes (2006) points out that there are environmental and microbiological standards for the discharge of effluents from water bodies in Brazil destined for countless activities of society that are defined by CONAMA Resolution 357/05 and that Ordinance 05/89-SSMA establishes standards for the emission of liquid effluents used to observe polluting sources. Table (1) presents the parameters used to calculate the WQI, their nomenclatures, and units of measurement. Table 1: Parameters used for quality determination Lopes and Junior (2010) describe the index as a weighted average in which multiple test results are represented in a single value from 0 to 100. This index is used as a tool for water quality assessment. It can be applied at various points in rivers and lakes over time, comparing them on a quality scale between poor and great. IV. R esults and D iscussions Using IoT, it is possible to create an information collection system on the water quality parameters from a Wireless Sensor Network (WSN) scattered in the space of a watershed, as exemplified by Figure (1), which represents the space of the Piracicaba, Capivari and Jundiaí Rivers Watershed, which has an area of approximately 15,377 km², being 92.45% in the State of São Paulo and 7.55% in the State of Minas Gerais. To calculate the WQI, many sensors, each with a specific purpose, would be distributed in strategic locations within the catchment area to collect the necessary information in real-time and transmit it to an information storage and processing center. Fig. 1: Simulation of wireless sensor networks to collect water quality parameters in PCJ Basins Given the variety and volume of information collected from each of the sensors, a database would be required to store the parameters received, and then send them to the Big Data application that would perform the analysis and WQI calculation based on the formula for calculating this indicator. Seeking to exemplify how IoT and Big Data can contribute to determining the water quality indicator, the parameters already described in Table 1 will be used. Based on the PH indicator, useful for calculating water quality, it is possible to identify the value using a PH transmitter that measures the acidity or alkalinity of a liquid. PH is calculated using a logarithmic scale with a range from 0 to 14, in which the value 7 corresponds to pure water, and values below 7 show the acidity of the water. In contrast, the values above correspond to basic (alkaline) water. Unlocking the Potential of Smart Watersheds: Leveraging Iot and Big Data for Sustainable Water Resource Management and Indicator Calculation