Software to reduce water loss in drinking water networks (Standard)

The software is intended to be a cloud-based and maintenance-free application, that allows water network operators to monitor their networks for leaks. As "state of the art" security, the cloud application is to be based on internationally valid standards.

The water loss management system is designed to be regularly updated by the supplier with new features and is used for the automatic backup and storage of data.

The system is designed to enable the user to implement a complete distribution network with different DMA's (District Metering Area) or PMA's (Pressure Metering Area), in which all inflows/outflows/pressures are measured.

The software should be able to record the flow or consumption in a DMA. These measurements are to be used to detect and locate events in the various DMA's.

In order to get an overview of the security of supply via the DMA's, it should be possible to create and calculate associated KPI’s.

The user should be able to define notifications/alarms through the included tools, the analysis should be performed automatically. The results of the analyses should be sent to the user/customer by e-mail or via other notification channels of the software.

Charts and analysis results can be exported as PDF or CSV files for further processing.

The system can perform a real-time analysis of the incoming data to detect problems in the water supply network as quickly as possible.

Advanced event management, based on artificial intelligence (AI) algorithms, makes it possible to detect many types of events such as leakage, trend, etc.

All sensor data from the connected sensors are available in the software. The user can analyze the sensor data (standard view, minimum night flow, average night flow, etc.). Various levels are available in the charts (expected value, previous year's figures, real-time analysis, integrated hardware alarms, curve history, etc.). Sensors can also be represented on a map.

The system should also be able to generate predictions such as expected values that can be compared to metrics to generate AI-based events.  This feature increases accuracy and takes also into account holidays, seasonal influences, weekends, etc.

In order to integrate the system into a complete solution, it must be possible to receive data directly from sensors or from a SCADA. The geographic data is extracted from the GIS, typically using shapefiles. In addition, it should be possible to integrate the system into intelligent business systems through a secure API.