The assumed outcome of the project is aimed at solving the problem related to the low intensity of continuous river water monitoring in Poland, Europe and the world, which is caused by the lack of technological solutions available on the market adapted to river conditions. The researchers aim to develop an Autonomous Internet of Things (IoT) System for Water Quality Monitoring and Operational Support for Hazard Identification (WaterSense - ASIR) adapted to river environment conditions, operating continuously.

- The project started as a collaboration between MAGLY and NEBUCODE. I, in addition to being a PhD student at WUT in CEZAMAT, run MAGLY, a company that develops a hardware solution. I proposed the project to the CEO of NEBUCODE, Patryk Pijanowski, then to IMGW (Institute of Meteorology and Water Management) and then just to CEZAMAT. In fact, the project started with an engineering thought and research, from which it emerged that we were not monitoring water quality at all. I then asked myself why we weren't doing it, what the reason was, where the limitations were - and that's where the idea for the Project came from,’ explains Filip Budny, Technical Engineering Manager of the Project.

The project is being implemented by an experienced interdisciplinary consortium consisting of the Warsaw University of Technology - Leader, IMGW-PIB (National Research Institute) and the MAGLY and NEBUCODE companies. The Warsaw University of Technology is represented by 20 scientists and the work is led by: Filip Budny (Project Technical Engineering Manager), Prof. Małgorzata Jakubowska (Project Manager) and Prof. Łukasz Górski (R&D Manager).

Three key elements

The WaterSense - ASIR system integrates three globally innovative components: Autonomous Metering Station, Intelligent Metering Station Management System and Interactive National River Pollution Risk Map.

WaterSense sensor

The station will represent a new generation of intelligent tools for monitoring water quality on a continuous basis. It monitors 10 key physicochemical water parameters such as pH, chlorides, nitrates(V), ammonium ions, orthophosphates(V), conductivity, oxygen content, water temperature, flow velocity and depth. Seven of these will be measured using the applicant's patented WaterSense technology, with a roller system module equipped with several hundred disposable and inexpensive miniature sensors that require no calibration or cleaning. When analytical performance is lost, the sensor is automatically replaced with a new one. Continuity of operation 365 days a year is ensured by a hydroelectric micro-generator powered by flowing water and heating of the electronics to ensure stable operation in winter conditions.

The smart metering station management system will be designed as an advanced comprehensive platform running on a cloud-based infrastructure for monitoring, management and analysis of data collected from autonomous metering stations. Its architecture will be based on a number of innovative modules, including, among others, a module predicting values of physicochemical water parameters, a module identifying anomalies in measurement data or a REST API module, which will allow free and intuitive connection and synchronisation of data generated and collected by the ICSZ-SP system with external databases. AI modules will predict water parameter values up to 72 hours in advance.

The interactive map, on the other hand, will be a modern and innovative tool aimed at providing up-to-date information on river pollution risk in the country. The map will be developed on the basis of publicly available data, which will be integrated, processed and analysed in terms of sectoral sources of pollution causing an elevated level of pollution risk for a given river section. The tool will be able to provide the information necessary for an accurate understanding of the ecological situation of rivers in different regions of the country. One of the key elements of the map will be the ability to present information in an integrated manner. Operators of the system under development will not only be able to check the level of pollution risk in a specific area, but also understand the causes of the pollution. For potential clients, such as local authorities, businesses or environmental organisations, the map will become a valuable source of knowledge and will enable them to identify vulnerable areas and the main types of pollution found in a particular region. The tool will support them in planning the location of measuring stations or measurement networks, the aim of which is to monitor water quality in an effective and representative way for the study area on a continuous basis.

- A commercialisation model based on the low cost of the measuring station and a subscription offer tailored to the needs of different consumers will make the developed system accessible to anyone interested.  Various entities will be the recipients of the solution developed under the project: water management and environmental protection institutions, water and sewage companies, local government units, but also enterprises of all sizes interested in continuous water quality monitoring. The first letters of intent related to piloting the effects of the project, have already been signed,’ Filip Budny points out.

The implementation of the project will contribute to achieving environmental, social and economic benefits. In the long term, WaterSense - ASIR will also avoid the spread of the threat and the run-off of polluted river water into the Baltic Sea, which is one of the most polluted seas in the world. At the same time, the tightening of environmental legislation may influence WaterSense to become a mandatory tool required by public authorities, which are the recipients of the solution, compounding the economic benefits in the years to come. In particular, the system will be permanently expandable with other modules measuring additional water physicochemical parameters, algorithms and functionalities, thanks to the appropriate design of the measuring station and the ICSZ-SP system architecture developed during the project phase. As a result, some of the assumptions will be able to be adapted in the future to handle other business and scientific issues involving real-time analysis of large amounts of data or prediction taking into account multiple variables.