DataGenie MDM

DataGenie is a 3rd generation Meter Data Management system built on big data technologies and machine learning-based data processing.

Key functions

  • It does not just process consumption values for billing purposes. It also collects and analyses data from the grid such as voltage, current, active/reactive power, meter events, even weather data.
  • It works with various types of devices such as smart meters, data concentrators, gateways, aggregation meters, feeder meters or RTUs.
  • It processes data about various parts of the grid such as consumption points, secondary substations, feeders or grid segments.
  • It contains algorithms for advanced data processing based on machine learning. These can cover the accurate estimation of missing values, complex validations, the detection and classification of behaviour patterns, pointing up anomalies and forecasting.
  • It offers a publish/subscribe mechanism to other systems which can obtain relevant low voltage grid data easily.



  • DataGenie architecture is based on stream processing (Kafka) and distributed database (Elasticsearch).
  • Stream processing recognises notable situations in incoming data, detecting them immediately and allowing timely remedial action to be taken.
  • A distributed database used offers a powerful mechanism for storing, querying and aggregating terabytes of data.
  • It is fully scalable and can be used both for small pilot projects as well as for large roll-outs.
  • DataGenie computation logic is able to work with missing or uncertain data, quite common with data from large sensor networks.
  • DataGenie data processing is controlled by a specialised engine which executes defined data processes.

DataGenie MDC

DataGenie-MDC (Meter Data Collection) system allows to effectively communicate and manage infrastructure consisting from various meters and sensors.

  • The DataGenie-MDC (Meter Data Collection) system allows data from an infrastructure consisting of various meters and sensors to be effectively communicated and managed.
  • DataGenie-MDC supports various modes of communication, push/pull modes, synchronous/asynchronous. It contains various communication protocol adaptors such as DLMS, web services, IEC 60870-5-104, VDEW or SNMP.
  • It communicates with smart meters, data concentrators, gateways, RTUs or power quality meters at substations.
  • It has a powerful communication control engine able to communicate simultaneously with tens of thousands of devices.
  • It supports communication operations such as reading profiles and registers, receiving events, sending TOU tables, remote device parametrization and the upgrading of firmware.
  • It monitors the availability of devices for communication and will evaluate the parameters of the entire communication infrastructure and any changes to it.

Field Installation Management

Installation of smart devices more effectively, faster at lower resources requires remote testing during large-scale installation campaigns. Using our proven DataGenie-MDC with additional field installation technology can identify if smart device is installed properly and communicate results with superior system.

Why Field Installation Management?

The goal of every smart device installation is to save time and effort and reduce error rate to zero by automating the process.

With tens of thousands of smart devices in distribution grid customers are looking for solution how to automate local installation check and verify communication setting and discovery of smart devices remotely. Field Installation Management automates, saves time and resources for massive smart meters rollout implementation by providing remote automated auditing services based on many testing scenarios.

Test your newly installed smart devices by using Field Installation Management and move them to production system easily.

Key Benefits

  • Avoid incorrectly installed smart devices
  • Save time and costs spent by personnel during component testing and waiting in field for testing results
  • Automate operating activities associated with migration installed components into production environment
  • Predict and report issues associated with non-compliance production plans, delivery, distribution and installation targets during testing and switching to production
  • Save human resources from repeated on-site installation trips to ensure the device is installed correctly