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Case Study

Process Automation for ColiMinder

ColiMinder is an IoT solution for water quality monitoring and reflecting probing results in real-time.

IoTManaged Delivery
Case image


Project overview

Project Duration:
March 2018 - September 2018
Technology Stack
MongoDB, AngularJS +

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.



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.

Platforms features
Usually, there are about 20 devices under admin control and it’s hard to keep in mind the exact location of each. That’s why we dedicated a separate tab for an interactive map which helps a support team to locate a problem or water contamination source and quickly fix it. The map shows all devices under control. Color markers indicate a device’s status in real-time. Upon clicking the marker, the admin gets full details about the issue.
Device management
From this panel, admins can connect new devices to the app, add reagents that are used by ColiMinder, and grant access to specific users.
Data processing & analytics
Some of the devices are located in remote, hardly accessible areas — for example, Great Lakes in Canada or closed industrial facilities. The web app serves as a remote interface and robust back-end processes metrics from a centralized database into comprehensive analytics.
A role-based access control system
We have integrated a role-based access control (RBAC) system that allows ColiMinder owner to manage user privileges within an app. Owners have full control over which data to share and what privileges to grant. By default, there are 5 user roles (Owner, Admin, Manager, User, Guest) in the web app. But there is also an option to create custom user roles if needed.
Notification Center
This part of the software was specifically developed to communicate with ColiMinder’s telemetry system. The module transcribes errors and warnings from the machine, then it categorizes errors by levels of importance, and automatically notifies a support team responsible for that kind of issue. Notification Center is fully integrated with RBAC system. Notification can be sent to the specific user group depending on their access level.
Help center
Due to the system’s complexity, it was required to add a dedicated tab where all educational material would be stored. The application supports various types of data so that educational materials of different formats, including images, pdf-manuals, and video content can be added.
Our development team successfully delivered the ColiMinder web platform, and it was gradually integrated into the existing network. As a result, the massive part of all the processes was automated, and the amount of manual work was so significantly decreased that it made our client consider launching this IoT solution to the market which they successfully did.
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