Machine learning added to Grape Solutions' IoT device management platform

Another milestone has been accomplished in the development of Grape Solutions' IoT platform, which is supported by the Hungarian Research, Development and Innovation Office. The first phase of the milestone aims to implement device management using machine learning; the development was successfully completed earlier this year.


Currently, more than 8 billion IoT devices are being used worldwide, and this could reach 30 billion by the end of 2030. Smart devices are widely used in different sectors, such as agriculture, retail, energy and transport infrastructure; therefore, IoT device management will be a key driver for all industries in the short term.

The project's objective was to develop a user interface that would allow more straightforward and more rapid integration with the customer's IT systems. For future enhancements, we prepared the system for the extension of additional protocols and integrated machine learning components to support on-premise operations.

Blog post - IoT EN - 1
As part of the first milestone, we connected the IoT platform functionality with our solution for energy communities, which uses machine learning to predict the expected consumption of the solar PV system; accordingly, residents are informed about the system's performance through reports and forecasts.

Grape IoT Platform features with the new improvements completed:

  • Rapid integration of devices
  • Quickly processing large amounts of device data
  • Remote control of devices
  • Flexible integration of existing systems
  • Indirect access to partner devices
  • Creating rule-based alerts and alarms
  • Scalable cloud and on-premise capable platform
  • Machine learning model adaptation to predict events that have not yet occurred