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 14 According to Trojan (2012), an important parameter is given by the flow measurement to help control water loss, including the size of lengths of pipes, and water flow control, based on adopted standards and thus assist in maintenance. Ferraz et al. (1998) contextualize the theme by pointing out that it is important to use industrial consumption indicators, which use water as a source of abstraction and urban release for good management of water resources. Gloria et al. (2017) note that the qualitative and quantitative monitoring of water resources is an excellent way to evaluate the water supply and support managers in making decisions regarding the multiple and integrated uses of water, including the concern with minimizing environmental impacts. c) The Contribution of ICT’s IOT and Big Data Neves (2021) describes the term Internet of Things (IoT) as being the interaction produced between everyday objects, which are connected through internet networks and systems, and are considered intelligent, due to the exchange, generation, and processing of data through wireless communication mechanisms, without the need for human intervention. Zabadal and Castro (2017) point out that, through the internet, it is possible to control them and exchange data between all connected points, devices, systems, and objects so that they have applications in various areas of society, such as health, cities, and smart homes, among others. Smart objects remain active in the system during the exchange of information, and their architecture is composed of four units: • A power source that feeds the components (such as rechargeable batteries or not). • Sensors for monitoring the environments in which the objects are inserted or that are acting and performing certain functions. • Processing and memory that stores the data. • Wired or wireless communication. In water resources management, applications involving Information and Communication Technologies (ICT) still need to be improved or, at most, inexpressive. In this sense, Tan (2016) highlights that, within the context of Industry 4.0, 55% of the Internet of Things covers the area of public services and the development of smart cities, while 45% is related to home appliances and vehicles. In a more recent study, Silva et al. (2022) suggests the validity and the potential of IoT and Big Data contribution to the processes of decision-making in the context of watersheds, which this article advances in the proposal and complements it. Complementarily, the exponential growth of the volume of data generated, especially in the context of smart objects and IoT, imposes the need to develop technologies capable of processing them proportionally and evolutionarily, as is the case of Big Data. According to Caldas (2016), the term Big Data expresses the data currently produced by society and focuses on processing large amounts of data, such as those from social media or sensor networks. In addition, Caldas (2016) emphasizes that Big Data platforms consist of a compilation of functions that act with a high power of data processing, allowing the interaction with stored data to organize them, applying computational techniques, and ensuring the highest possible quality. Big Data, for management and decision-making processes, is characterized by the junction of five properties: Volume, which is related to the amount of data available for processing; Variety of sources and types, including structured and unstructured information; Speed with which information arises and accumulates; Veracity of data and information generated; and finally, Value that is added to the data, which after processing becomes useful and valuable information (TAURION, 2013). III. M ethodology The methodological procedures involved documentary and bibliographical research with an exploratory approach. Since the subject still needs to be explored, it is necessary to obtain references to the use of IoT and Big Data to assist in calculating useful indicators for managing water resources (Gil, 2008). The conceptual elements exposed here aim to provide greater familiarity with the theme of intelligent watersheds and thus make it better known (SAMPIERI, COLLADO & LUCIO, 1991). To exemplify how IoT and BIG Data can contribute to data collection and analysis of indicators in “smart river basins,” the Water Quality Index (WQI) will be considered due to its importance and relevance. The IQA was created in 1970 by the National Sanitation Foundation (NSF) in the United States and, later, was used by the Environmental Company of the State of São Paulo (CETESB) in Brazil (ANA, 2022). According to Gloria et al. (2017, p. 3), the reference made to water quality does not concern “only the state of purity of the water, but the physical, chemical and biological characteristics and, depending on these characteristics,” the various destinations that will be given to it to the analyzed water. Water quality is demonstrated, therefore, from the set of quantitative measurements of certain substances found in the observed sample. Almeida and Schwarzbold (2003) explain that the WQI was developed to assess raw water quality to make it available for public supply after treatment. The parameters used in calculating the WQI indicate, for the most part, the contamination caused by the disposal of domestic sewage. Nine variables considered the most relevant for the calculation of the WQI are collected: dissolved oxygen (% Saturation), fecal coliforms (Coli Unlocking the Potential of Smart Watersheds: Leveraging Iot and Big Data for Sustainable Water Resource Management and Indicator Calculation