We just started work on RoBétArmé – a new project funded by the European Union

We are part of a large consortium of 19 partners from 12 Member states who will work together to deliver a human-robot collaborative construction system for shotcrete digitization and automation through advanced perception, cognition, mobility and additive manufacturing skills. 

Digital Systems 4.0 is looking after the user-driven development and evaluation of the software systems, applying the lessons learned in previous EC projects such as iHelp.

The pre-kick-off meeting took place in June 2022 as a Teleconference and we are now looking forward to meeting the partners personally at the kick-off meeting in Thessaloniki in July 2022.

Off to a good start 😊

Working on a new EC project – European Connected Factory Platform for Agile Manufacturing

We are pleased to announce that we have received cascade funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825075 for developing a TeamCreator module and integrating it into the Industry 4.0 platform of services provided by EFPF.  This will increase the visibility of our products and services through collaborating with cutting-edge companies throughout Europe.

Starting the journey to personalised e-help

We were delighted to meet our partners from across Europe during the iHelp kick-off meeting last week.

DigiSys 4.0 will contribute to developing software which is tuned to the needs of its users – patients, clinicians and health service managers. 
We are to ensure the software produced by iHelp is user-friendly and “sticky”, avoiding the usual loss of interest by users in our health application after a few days.  We will use a combination of user-centred design and personalised nudge messages develop through our collaborative research with University of Manchester.

We just completed an exciting analytics project with one of the biggest on-line reverse logistics companies in Europe

We used advanced data analytics techniques over millions of customer purchase records to analyse consumer behaviour related to on-line returns.  We clustered consumers into different categories depending on their net value to the on-line retailer, the amounts purchased and the percentage of goods returned.  This analysis will help our customer identify fraudulent behaviour and maximise profit for their clients.

If you would like to use our expertise for similar tasks, please contact us.

Look at our new logo!

Exciting times with a new EC project to focus on Personalised early risk prediction using Artificial Intelligence and Big Data technologies!

A new EC funded project called iHELP will apply AI and big data technologies to perform early risk prediction of Pancreatic Cancer.