FLEX4RES will utilize platform-based manufacturing that builds on the state-of-the-art Gaia-X and IDS technologies for data-sharing in the horizontal supply chain and the Asset Administration Shell (AAS) that is to implement intra-factory reconfiguration practices. FLEX4RES considers the Digital Twin of the value-adding network a key enabling technology to achieve reconfiguration processes in highly flexible production systems and networks. The key element of technology linkage is represented by the Self-Descriptions with linked, standardized information models, especially in terms of resilience. The developed platform and specialized hardware aim to improve the existing industry-established lean management approaches related to Reconfiguration Management through the digitalization of the production, characterized as Industry4.0, by allowing for the information sharing between value chain stakeholders.

Type of Action: HORIZON-IA
Proposal number: 101091903
Duration: 36 months


General Architecture for a Multilingual Information Retrieval system

As the computation power is increasing and cost of storage is decreasing, the amount of day-to-day data we deal with is growing exponentially. According to IDC, the total data in the world by the end of 2021 will reach 74 zettabytes. In fact, IDC predicts the world’s data will grow to 175 zettabytes in 2025. If you attempted to download 175 zettabytes at the average current internet connection speed, it would take you 1.8 billion years to download. But without a way to retrieve the information and to be able to query it, the information we collect doesn’t help.IR systems help understanding the data and transforming it into knowledge. Many applications extending from search engines to genetic researches use information retrieval systems in combination with machine learning algorithms to produce relevant results.The proposed project idea; GAMIR(General Architecture for a Multilingual Information Retrieval System) offers a reference IR framework so that cutting-edge AI algorithms and NLP techniques can be used to refine the results of multilingual informational queries on different types of contents. The framework extracts the features of populated documents by using different AI models for different content types. These features are indexed in different language indexes and the elements of results are post-processed to refine the results of the query. Below is a very high level diagram showing the components of GAMIR framework.
The project also demonstrates the use of the framework by different use cases such as multilingual text, image and video queries which will help to make more qualified and detailed searches and search within media.

Overall, the GAMIR project is an initiative to unify the efforts of European countries to employ their own NLP and AI based tools in cooperation to create and lower the barrier of implementing IR related applications.

Information retrieval systems are the basis of many state of art automated applications. The main application area of IR systems are search engines.

Today, Google dominates the entire search market by %91 penetration. There are also other important search engines in the Far-East region, like Baidu in China, Yandex in Russia and Naver in South Korea. These search engine companies have some billion USD market caps. On the other hand, their engagement with users make these companies important players in digital markets since they have vast knowledge on user identity.

When we look at Europe, we see some initiatives like Qwant and Seznam that try to encompass nationwide search engine needs. However they are not yet big enough to cater the requirements of different European countries.

Moreover, GAMIR is not only a framework for search engines but also a general framework for other IR related applications like voice assistance, context based queries and other types of applications.

Project Status: set-up

Start Date: September 2022

End Date: August 2025

Budget (total): 5101.48 K€

Effort: 109.77 PY

Project-ID: C2021/2-3


Agro Insurance Data Management Platform with API Services

Agricultural insurance is a global, fast-growing billion-dollar industry and, due to the effects of climate change, it is becoming more important every day. Effective insurance policies stabilise farm income, reduce poverty and ensure a climate safety net for food producers. SmartAgroInsurance aims to develop a Smart Agriculture Insurance Data Management Platform to provide, analyse and integrate agricultural data from different sources with insurance industry know-how so that insurance companies can achieve better premium calculations, claim automation and fraud prevention and provide supportive, damage-preventing advice to the farmer.


Environment Adaptive Recommendation System

The main problem of many domains is the lack of information and leading, as potential customers cannot be reached because there is not enough information and guidance towards the right products. The EARS project aims to bring together all parties in the value chain, creating an ecosystem, providing a new platform that fits the purposes of all parties, and enabling them to collaborate. Entities such as businesses, algorithm developers, solution providers, service providers and Recommendation Systems are brought together to enhance their/others capabilities, monetizing the artifacts through utilizing them as a service.

EXPAI SmartIndustry

Integrating AI into smart control systems, and increasing productivity for industrial areas

Smart technologies getting higher importance while supporting Artificial Intelligence technologies that we use in our life. The main goal of this project is to provide a flexible, controllable digital environment supported by Explainable Artificial Intelligence digital smart platform that will collect and analyse sensor data from various resources for different domains and these will be combined in a common framework in industrial areas and Retail Market. The project will present novel methods and solutions the industrial market and real-life use cases for exploitable solutions.


AI-Powered Communication for Health Crisis Management

The objective of AIcom4Health project is to offer an innovative solution towards recovering the pandemics negative impacts on public health ,healthcare access and socioeconomics through remote monitoring -AI based platform’s integration to the public’s daily life whereas employing healthier citizens for smart cities s in the area of 5G and beyond, network slicing, edge computing, artificial intelligence and machine learning based on feasible use cases including both medical and non-medical sensors for making accurate decisions and predicting risks against contagion in the future. The use cases include integration of an IoT platform with various types of sensors to monitor physiological, behavioral and environmental data from natural indoors and outdoors environments.

From a research perspective, AICom4Health aims to bring together data processing, AI and data communication techniques. Edge computing paradigm is a key enabler that integrates data processing and artificial intelligence algorithms within data communication, 5G, network slicing and IoT domains in order to provide reliability and timeliness in the system. Use cases within the AICom4Health project will provide continuous monitoring of individuals and crowds through multivariate analysis, fast response and action to health deterioration of individuals or health threats within a crowd. It also deals with big data collection from several measurement surveillance cameras and also air quality monitoring capabilities. This will require real-time, fast and intelligent data processing techniques, while providing highly reliable communication through network slicing.

Project Status: running

Start Date: January 2022

End Date: May 2025

Budget (total): 5114.94 K€

Effort: 73.52 PY

Project-ID: C2021/1-7