ECSEL-project DAIS, Distributed Artificial Intelligence Systems

The Oslo-based partners Jotne EPM Technology, Step Solutions and Expert Analytics are taking part in a 3-year pan-European investment to develop the next generation of smart solutions for artificial intelligence (AI). Jotne EPMT, Step Solutions and Expert Analytics in conjuction with strong European partners will develop new industrial solutions that move AI closer to the production processes - the next big step in the implementation of Industry 4.0. This is especially important for remote facilities (e.g hydropower, shipping, offshore and transportation) with limited access to data communication. As a part of the EU-project Distributed Artificial Intelligent Systems - DAIS the Norwegian partners have the main responsibility for the development and execution of an industrial demonstrator aimed at the health monitoring of hydropower systems. The DAIS project has an overarching goal of strengthening Europe's position within distributed artificial intelligence and covers all aspects from sensors, control systems analysis and communication to security, smart data storage methods and feedback-systems. This is a comprehensive project that involves 47 actors from 11 European countries and with a total investment of 360 million NOK. The main focus of the partners have been to identify the specific requirements for DAIs overall, and for the specific use-cases.

The DAIS project aims to strengthen Europe's position within distributed artificial intelligence (AI). At the present, data analysis mainly takes place in cloud-based systems and thus at a separate location to where the data is produced and collected. This leads to AI being applied outside of the systems it is meant to improve. The solution is to place AI at the level where the data is generated, such that analysis, support for deciscions and process control takes place as close as possible to the monitored activity. The impact of this is that processes can be improved locally, automatically and in real time. Depending on the state of the market, this can have a disruptive effect and be a major competitional advantage if applied. The technology shall be based on open standards and be developed within the framework of existing industrial requirements both for hardware and software. The Norwegian use case will collect, process and analyze audio data from a running water turbine in order to optimize start-stop cycling of the machinery. The analysis will be done by AI connecting to a product lifecycle management software framework. The output from the analysis will be fed back to hardware connected to the system in order to facilitate optimized regulation.