| Abstrakt: |
Rivers serve as vital resources for human communities and ecosystems, necessitating precise and continuous monitoring to ensure their health. Rivers are subjected to contamination by numerous chemical, physical and biological pollutants. Water quality assessment is a process wherein experts and researchers from organizations such as environmental agencies and universities traditionally measure parameters affecting water quality, such as water temperature, pH, transparency, turbidity, dissolved oxygen, nitrate levels, among others. Subsequently, the Water Quality Index (WQI) is calculated according to specific standards, such as IRWQIsc and NSFWQI. The objective of this paper encompasses two sections. In the first section, using the Delphi-Fuzzy method, we identify parameters critical to water quality assessment, the existing challenges in traditional methods, and new requirements based on artificial intelligence and IoT technologies. This was accomplished with the assistance of selected experts using the snowball sampling method from relevant organizations such as the Environmental Protection Agency and the Water and Sewerage Department. The data analysis results, processed by appropriate softwares, indicated that the measurement of heavy metals and chlorophyll-a ranked the highest and the lowest in priority, respectively. Additionally, challenges such as outdated water quality assessment practices, high assessment costs, significant errors, and a shortage of expert professionals in organizations were identified. Furthermore, all experts agreed that the current traditional methods are inadequate for meeting new requirements, such as automated pattern extraction and parameter prediction, which can be achieved with an intelligent assistant. In the second section of the paper, an IoT-based method for measuring the critical and prioritized parameters in river water quality assessment is proposed, designed, and implemented. The proposed system consists of four layers: perception, network, platform, and application. This system was installed and operated in a real-world river environment. The proposed system not only addresses the issues present in traditional methods used by organizations but also meets the new requirements. [ABSTRACT FROM AUTHOR] |
