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The proposed architecture consists of three layers, viz a sensor-dependent data pre-processing layer, a sensor-agnostic ML layer for converting data into information, and an application-specific layer for knowledge extraction. There are two major merits of the work. By having a layered, the architecture can easily be repurposed for different industries. Secondly, this agility in the architecture also facilitates the changing of sensors as well as overall goals of the architecture.The project aligns with Primus' digitization goal and offers a flexible solution applicable to multiple industries, promoting sustainability, data-sharing and architecture sharing. By developing DIPy-AI, the project aims to provide a scalable and adaptable solution for sensor data processing for industries.

Research Area

  • Elektroteknik och elektronik

Research environment / Institution

  • Produktionsteknik
  • Primus (KK-miljö)
  • Institutionen för ingenjörsvetenskap

Project leader

Research Partner

  • AP and T
  • GKN Aerospace

Research funding

  • KK-Stiftelsen

Project time

2024 - 2027