The FIREMAN proposal (Framework for the Identification of Rare Events via MAchine learning and IoT Networks) which was submitted, with AIT’s participation, to the “Big data and process modelling for smart industry – BDSI” 2017 call of the CHIST-ERA program, was recently recommended for funding. FIREMAN is coordinated by Lappeenranta University of Technology in Finland and further comprises, besides AIT, of University of Oulu in Finland, CTTC and SEAT in Spain, and Trinity College Dublin in Ireland.

AIT participates via both its Broadband Wireless & Sensor Networks Group and its Big Data Mining Group and is in charge of FIREMAN’s fundamental studies, led by Professor Papadias, who will also act as the project’s Technical Coordinator, and artificial intelligence algorithms for the detection and prediction of rare events, led by Professor Christou.

The project is expected to start within the 3rd quarter of 2019, after formal funding approval by the national research funding organizations of its partner countries.

Project objectives: The overall objective of FIREMAN is to design, develop and showcase a novel big-data based framework that encompasses all steps from sensing and data acquisition to statistical analysis and operational decisions, to accurately identify, detect, forecast and prevent rare events in a pre-determined industrial physical process. The proposed approach will be demonstrated on SEAT’s automotive manufacturing plant in Spain, as well as on University of Oulu’s 5G test network and Nokia’s base station factory in Oulu.

About CHIST-ERA: CHIST-ERA ( is a program for European Coordinated Research on Long-term Challenges in Information and Communication Sciences and Technologies. It is a coordination and cooperation activity of national (and regional) research funding organizations mainly in Europe and is supported by the Future and Emerging Technologies (FET) program of the European Union through the ERA-NET funding scheme. Its aim is to reinforce the transnational collaboration between the participating states in challenging multidisciplinary research in the area of ICST with the potential to lead to significant breakthroughs.