Open and Cost-Effective Digital Ecosystem for Lake Water Quality Monitoring

In some sectors of the water resources management, the digital revolution process is slowed by some blocking factors such as costs, lack of digital expertise, resistance to change, etc. In addition, in the era of Big Data, many are the sources of information available in this field, but they are often not fully integrated. The adoption of different proprietary solutions to sense, collect and manage data is one of the main problems that hampers the availability of a fully integrated system. In this context, the aim of the project is to verify if a fully open, cost-effective and replicable digital ecosystem for lake monitoring can fill this gap and help the digitalization process using cloud based technology and an Automatic High-Frequency Monitoring System (AHFM) built using open hardware and software components. Once developed, the system is tested and validated in a real case scenario by integrating the historical databases and by checking the performance of the AHFM system. The solution applied the edge computing paradigm in order to move some computational work from server to the edge and fully exploiting the potential offered by low power consuming devices.

Automated summary

In certain sectors of water resources management, the progress of the digital revolution is hindered by factors such as costs, lack of digital expertise, and resistance to change. This project aims to examine the feasibility of using an open, cost-effective, and replicable digital ecosystem for lake monitoring to address the issue of incomplete integration of information. By utilizing cloud-based technology and an Automatic High-Frequency Monitoring System (AHFM) built with open hardware and software components, the system will be tested and validated in a real-life scenario, integrating historical databases and evaluating the performance of the AHFM system.