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ColiMinder is an IoT solution for water quality monitoring and reflecting probing results in real-time.
Vienna Water Monitoring needed radical improvements to their microbiological water quality monitoring system called ColiMinder. Because of the system’s complexity, most of the devices had been previously maintained by the client’s support team. The amount of collected data was so great that our client had to keep an entire R&D team to be able to manually process those data. And because of that, the bandwidth was somewhat limited and Coliminder couldn't obtain real-time results of data probing. We were hired to create a web application that would turn ColiMinder’s hardware into a market-ready product and help the support team to maintain the system.
When we were starting the project, our development team faced several issues:
- big batches of raw data – the system collects data on more than 40 water-specific parameters and each has its own variations. Altogether, it creates a vast data layer that updates every 10 seconds;
- complex telemetry system – ColiMinder also has a telemetry system, the information from which has been provided by the middleware in a form of machine codes that only the client's R&D team could understand.
Considering the importance of the collected data and the lack of tech capabilities of the existing ColiMinder system, our team defined weak spots and developed the range of significant improvements for smooth platform operation. The client’s hardware had 5 different work phases but the interface maintained only one, so we added 4 more work phases with background processing of raw data. We also added statistics about the overall system performance. Moreover, our specialists designed a device management area for easy modifying of microbial samples every connected device collects. Thus, our client got the solution that collects and processes live data from up to 100 devices.
SYSTEM ARCHITECTURE
Comprehensive scalable platform
Due to the system complexity, its architecture is built in a way to ensure maximum platform scalability. The robust back-end accurately processes information from a centralized database into comprehensive analytics and sends this data to the interface in the form of charts and reports. The algorithm of interactions between all of the architecture components allows collecting and operating live data and providing users with necessary crucial information in real-time.