Abstract

The existing procedure to analyze the potability and contamination levels of the Rural Potable Water (APR) systems has deficiencies such as only a monthly sampling, low budget and a system without continuous surveillance. This work proposes a real-time analysis and monitoring system of the main variables that determine the quality of drinking water in an APR, a low-cost system capable of delivering timely information. To achieve this, the main variables that determine the quality of drinking water are addressed, the appropriate sensors, the communication system, programming, obtaining a virtual microbiological sensor based on artificial intelligence, data processing in the cloud and validated the results at the prototype level. The sensors used are pH, conductivity, turbidity, total dissolved solids (TDS), temperature and oxidation reduction potential (ORP). For microbiological analysis, an important and complex factor, the indicated sensors have an unattainable cost for APRs. Here we propose an intelligent virtual sensor based on a fuzzy system to determine possible microbiological contamination, which uses turbidity, ORP, temperature and TDS values ​​as inputs. Data acquisition is done with the low cost IoT system, an Arduino and a RaspberryPi. Node Red is used for programming, the IMB Cloud platform is used for cloud computing, and Entel's 3G network is used for communication. Finally, a prototype is implemented where the proper functioning of the entire system is checked.