Dynamic and Statistical Modeling Used to Identify Critical Points in Water Resources Through IoT Sensors at Universidad de las Fuerzas Armadas ESPE
摘要
IoT sensors in monitoring drinking water and wastewater networks have transformed the hydrosanitary area at Universidad de las Fuerzas Armadas ESPE since real-time monitoring of an extensive system was accessed through a network of actuators and platforms. Four flow meters have been installed in the administrative and academic facilities. Through these devices, flow data were obtained in liters per hour (L/h), and the information stored in digital platforms allowed modeling of the behavior of water resources in space and time. It was determined that in the year 2023, the day of the highest consumption was Tuesday, with an average flow of 3,184.58 (L/h); the university population was 11,059 students and administrators; the critical points or considered hours of most significant demand were at 14:00, and 16:00 h and the hours of most significant loss in pipes and sanitary appliances were at 02:00 and 00:00 h, all the results were obtained with methodologies by information processing such as Rstudio, Python, and Vensim. Water losses based on the IoT flow meters installed were 28.17%, and based on the mass balance of water entering and leaving the University was 43.56%.