DIPy-AI - DIKW Pyramid-based Agile AI Architecture for Sensor Data Processing
The project proposes DIPy-AI, an agile AI architecture based on the data-knowledge-information-wishdom (DIKW) pyramid, for processing sensor data in production environments. It aims to address challenges related to data assimilation, quality detection, and modular information extraction.
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