ITEA is the Eureka RD&I Cluster on software innovation, enabling a strong international community of large industry, SMEs, start-ups, academia and customer organisations to collaborate in funded projects that turn innovative ideas into new businesses, jobs, economic growth and benefits for society. ITEA is industry-driven and covers a wide range of business opportunities facilitated by digitisation, such as smart mobility, healthcare, smart cities, energy, manufacturing, engineering and safety & security. ITEA pushes important technology fields like artificial intelligence, big data, simulation and high-performance computing into concrete business applications.
With pleasure we present you the ITEA Annual Report 2021, covering the results achieved in the period January - December 2021.
ITEA in numbers
Click on the figure for more informationFunded Call size in € m
Time from project idea to project start in months
ITEA Project Landscape
Project leader satisfaction survey
Results and improvement priorities
ITEA improvement priorities and results 2021
ITEA improvement priorities 2022
ITEA and Eureka
Positioning of Eureka, the ECP and ITEA
ECP bodies and activities
Introducing the new projects
ITEA 3 Call 7 Projects
Comrade - 20008
COMmunicate and collaboRAte in extendeD rEality
- Project leader
- TNO (NLD)
Traditional video conferencing tools come with limitations that prevent efficient and meaningful remote communication and interactive participation. The global pandemic and climate change urgently demand an era of eXtended Reality (XR) communication and collaboration. The aim of the COMRADE project is to specify, develop, integrate and validate end-to-end networked solutions for real-time communication and collaboration in XR. The project goal is to enable XR videoconferencing and meetings, virtual travelling, expertise at a distance, virtual studio productions, virtual home improvement and shared media and entertainment.
OMD - 20003
Optimal Management of Demand
- Project leader
- Experteam (TUR)
Increasing demands and time pressures accelerated by the pandemics make organizations ask for new automations to proactively manage their environments. The OMD framework produced in this project helps businesses to assign the correct agent to a specific service demand effectively, and remotely. This will shorten the time and reduce the cost of operations avoiding repetitions. The OMD framework will rapidly contribute to many sectors effectively using AI models to improve service as a CSM approach. Improving the overall efficiency of operations on the supply side, the project also increases customer happiness.
NGAST - 20013
Next Generation Automated Security Testing
- Project leader
- ARD GROUP (TUR)
IoT device manufacturers and operators face the challenge of defending a vastly larger attack surface with essentially the same resources. Methods and tools for automated security testing are needed to eliminate security weaknesses lurking in software or APIs. NGAST will tackle these challenges by creating methods to automatically identify software bugs leading to security vulnerabilities and an open, extensible platform where these methods can be easily applied. NGAST’s goal is to develop a next-generation CI/CD-capable automated security testing solution for source code, binaries, and distributed systems in the Internet of Things (IoT).
ENTA - 20020
Encrypted Network Traffic Analysis for Cyber Security
- Project leader
- Solana Networks (CAN)
Today, more than 80% of Internet traffic is encrypted and there is a strong need for innovative research and development of tools able to provide visibility into encrypted traffic and detect cyber-attacks. The ENTA project will explore three solutions based on Encrypted Network Traffic Analysis (ENTA) to: identify encrypted applications, Encrypted data exfiltration and encrypted Rogue IoT devices. The ENTA project will deliver an encrypted traffic analysis service platform for cyber security that will support a number of basic building blocks necessary for any ML/DL based traffic analysis.
SmartDelta - 20023
Automated Quality Assurance and Optimization in Incremental Industrial Software Systems Development
- Project leader
- RISE - Research institutes of Sweden (SWE)
Too often it is observed that as a system is being built and incremented with new features, certain quality aspects of the system begin to deteriorate. Therefore, it is important to be able to accurately analyze and determine the quality implications of each change and increment to a system. To address these challenges, SmartDelta builds automated solutions for quality assessment of product deltas in a continuous engineering environment by providing smart analytics from development artifacts and system execution, offering insights into quality improvements or degradation of different product versions, and providing recommendations for next builds.
HeKDisco - 20030
Healthcare Knowledge Discovery
- Project leader
- Mantis (TUR)
HeKDisco proposes a novel knowledge discovery process in health care systems that will provide physicians with reliable evidence on various treatment stages and clinical events, thereby reducing individual clinical errors. HeKDisco, following evidence-based medicine (EBM), aims to use the best (reliable) evidence in making decisions about the care of individual patients so that clinician’s experience, patient’s values and preferences, and the best empirical clinical guidelines are integrated. HeKDisco aims to transfer big health data from volume-based to value-based by generating a relational knowledge base that can lead to innovative treatments, predict therapeutic outcomes, and early diagnosis.
V-Space - 20039
Hybrid workspaces for humans and (semi-)autonomous vehicles
- Project leader
- SparxSystems Software GmbH (AUT)
Autonomous vehicles are being utilized by many industries such as agriculture, retail, mining, manufacturing. The aim of the V-Space project is to bring a unified solution for hybrid workspaces where humans and AVs collaborate together. The project has two complementary use cases focusing on ports and private spaces. Autonomous transports within ports is a key enabler for more intelligent and sustainable ports, forming the basis for predictable and cost-efficient operations. Similarly, there are large opportunities to be gained especially in smaller warehouses and other private spaces exploited by companies.
ASSIST - 20044
Automation, Surgery Support and Intuitive 3D visualization to optimize workflow in IGT SysTems
- Project leader
- Philips Medical Systems Nederland B.V. (NLD)
Current software image-guided therapy applications to assist the physician still require significant manual user interaction while all attention should go to the patient instead. The ASSIST project will develop technologies and solutions to get the physician back in control of the clinical procedure by assisting or automating part of the physician’s tasks during image-guided therapy procedures. The aim of the project is to optimise and simplify the workflow in image-guided therapy procedures with the main goal of streamlining physicians’ work, optimising imaging systems, improving patient outcomes, reducing human error and lowering costs.
VRCare - 20048
Virtual Reality Healthcare Simulations
- Project leader
- Lapland University of Applied Sciences Ltd. (FIN)
Despite the rapid development of Extended Reality industry (XR), there is a lack of high quality, certified training and simulations for healthcare professionals. The VRCare project responds to these needs by co-creating the first healthcare XR ecosystem across Europe which employs a holistic approach to XR healthcare simulations by combining: strong technical knowledge, service design, AI and machine learning, hand-tracking, natural language processing, pedagogical design, research and certification. The VRCare aims to improve the overall healthcare performance and make a positive impact on patients’ lives by reducing the number of mistakes professionals make.
Secur-e-Health - 20050
Privacy preserving cross-organizational data analysis in the healthcare sector
- Project leader
- Kelvin Zero (CAN)
Sensitive health data is often kept in silos in a way that cannot be efficiently leveraged for legitimate medical, research and data analysis purposes. The goal of the Secur‐e‐Health project is to integrate new approaches for digital ID technologies and privacy-preserving analysis techniques in a secure system infrastructure. The Secur-e-Health system allows medical institutions of all types to collaborate together and leverage data analyses and insights. This is expected to have a significant impact on the quality of the medical predictive models, the efficiency of data-driven treatments, the acceleration of new clinical research, and the improvement of healthcare in general.
SIGNET - 20052
Sensing and Image-Guided Neurological therapies, cardiac Electrophysiology and Tumour treatments
- Project leader
- Philips (NLD)
The overall objective of SIGNET is to develop efficient image-guided treatment workflows to replace currently complex procedures in cardiology, oncology and neurology. We develop systems and technologies, AI-enabled products and solutions, necessary to ultimately realize the North Star of single-episode, personalized, dose-adaptive, high-precision Magnetic Resonance guided treatments and interventions. These technologies and solutions aim to improve patient comfort, safety, treatment outcome, staff availability and economic viability. We focus on use cases where alternative image guidance approaches are either not feasible or where the value of direct MR visualization is obvious.
InnoSale - 20054
Innovating Sales and Planning of Complex Industrial Products Exploiting Artificial Intelligence
- Project leader
- Software AG (DEU)
InnoSale aims to innovate today’s sales systems and processes for complex and variable industrial equipment, plants and services that require time-consuming back-office support. InnoSale develops methods to increase the expressiveness of validation rules and to suggest relevant purchase options (case-based reasoning). Sales engineers will be supported in finding previous customer requests & orders and other suitable solutions quickly as well as identifying similarities between customers (evolutional clustering). User experience will be improved supported by combining deep learning systems with augmented reality techniques, 3D modelling and 3D printing.
Joint Eureka Clusters AI Call 2021 Projects
ATTENTION! - AI2021-023
Artificial Intelligence for Trade-based Money Laundering Detection
- Project leader
- RisikoTek Pte Ltd (SGP)
We are facing a new type of ‘pandemic’ in which $450 billion of illegally gained revenue is entering the genuine economy per year. Globally, we are lacking a science-based understanding of how illicit transactions can be detected and what patterns they follow. The ATTENTION! project will analyse the largest trade database of imports and exports available globally and will use AI/ML models to derive patterns of illicit trade activity. The ATTENTION! application will enable end-users to check transactions for potential smuggling, fraud and tax evasion.
AI FORSchung - AI2021-065
AI for fiber-optic remote sensing
- Project leader
- Philips Electronics Nederland BV (NLD)
The overall objective of AI FORSchung is to accelerate innovation and the growth of fiber-optic sensing by augmenting innovations in large-scale signal and data analysis with cross-domain validated AI methods. These industrial-grade embedded AI technologies are necessary enablers of advanced, robust and widely accessible fiber-optic sensing applications in the biomedical, construction, environmental and utilities sectors. Resulting implementations will advance the adoption of fiber-optic sensing across the spectrum of applications and open up new fields through cost-effective and easy-to-use products that extract rich, important information from fiber-optic data.
IWISH - AI2021-066
Intelligent Workflow optimization and Intuitive System interaction in Healthcare
- Project leader
- Philips Medical Systems Nederland BV (NLD)
Clinical procedure scheduling in operating rooms and image-guided therapy in labs is challenging because these spaces are complex, dynamic and often time and resource-constrained. Their unpredictability often leads to inefficient usage of scarce healthcare resources. The IWISH project will develop new technologies and introduce novel applications to simplify workflows and predict procedure duration in such environments with the main goal of streamlining physicians’ work. IWISH will focus on room and hospital level solutions, addressing data and AI-enabled solutions for clinical procedure optimisation and operational efficiency in particular.
SAIP - AI2021-083
AI For AgriFood Supply Chain
- Project leader
- Smartmind Veri Yonetimi Teknoloji Hizmetleri Anonim Sirketi (TUR)
A resilient supply chain is essential, especially in agrifood, and this can only be achieved with true visibility, transparency, collaboration and trust. The SAIP project helps suppliers to avoid problems by offering AI machine learning capabilities to empower them with an advanced warning infrastructure for delayed orders. In addition, the solution offers cycle time estimates that provide predictions on the probability of events that may occur. This creates a secure, shared and singular version of the truth for B2B transactions using blockchain technology.
SentioCura - AI2021-085
AI for geriatric and pediatric users at risk for cognitive impairment and learning disability
- Project leader
- Symptoma (AUT)
With an ever growing world population aged 60 or above, there is a pressing need to keep the elderly mentally healthy and cognitively fit enough to participate independently in daily life. At the same time, we are obliged to ensure that children are equipped to face and solve the issues of tomorrow. SentioCura will provide an AI-powered health assistant which enables screening, early recognition and intervention, engages children and the elderly through gamified cognitive training, monitors cognitive wellbeing and provides an overview to caregivers and health professionals.
EXPLAIN - AI2021-086
EXPLanatory interactive Artificial intelligence for INdustry
- Project leader
- ABB AG Forschungszentrum Deutschland (DEU)
In industrial settings, AI holds the potential for significant improvements, such as energy-efficient operations, increasing throughput and more sustainable operations. To realise the possible benefits of AI in industrial applications, close collaboration is needed between AI use-case providers, AI providers and research actors with backgrounds in machine learning, XAI, software engineering, user experience and human factors. The EXPLAIN project seeks to realise an end-to-end ML lifecycle which is interactive and explainable for industrial domain experts and will consider a representative set of industrial AI cases to develop generally applicable solutions.
AiECHOES - AI2021-089
AI supported Early-risk prediCtion and intervention of Health cOnditions with pErsonalized Sensors
- Project leader
- VESTEL Savunma Sanayi A.Ş. (TUR)
Every day, thousands of people need continuous monitoring of their health. AiECHOES envisions an innovative solution in the field of telemedicine which applies Early Warning Scoring & Emotional Recognition to clinical deterioration for patients beyond the hospital through a complete sensor network for remote patient monitoring and data analysis-based computing. This will prevent severe clinical deterioration for risk patients through early detection. As an added value, the healthcare system will also benefit by reducing the number of expensive intensive treatment periods, which implies huge savings.
Deep4sat43 - AI2021-098
Deep4Sat43: Geo-AI Ecosystem for tree (43) health inspection and early warning.
- Project leader
- Spectro-AG (NLD)
Changes to the climate and regulations requires orchard farmers and forest managers to take actions using timely, strategic innovation tools. Conventional disease monitoring and control is often based on the human factor and is therefore limited by small spatial coverage and inevitable subjectivity. Deep4sat43 will test and utilise deep learning algorithms in scenarios with different sizes/geographic locations/soil types/plant types/access to data/legal requirements in Spain, Portugal, Turkey, the Netherlands and Denmark. As a result, we will deliver a UX-friendly SaaS service for automatic early monitoring and early warning of crop diseases.
FAMILIAR - AI2021-112
Holistic Federated AI Development for Mixed-Reality Applications in Europe
- Project leader
- consider it GmbH (DEU)
The term ‘federated machine learning’ (FedML) is popular in the context of publicly funded R&D projects. Still, it is rarely used in industry, least of all in combination with other leading technologies such as XR and AM. FAMILIAR wants to create FedML solutions using head-mounted displays (HMDs). The solution shall be embedded and tested in real-life applications, such as automotive engineering, maintenance & training, welding and human-robot collaboration. To establish the use-cases, sophisticated data mining techniques will be combined with deep learning.
Activities and Events 2021
Online ITEA PO Days 2021
Cyber Security & Cloud Expo
Cyber Security Day and Smart City Day 2021
ITEA Customer & End-user workshop on Smart Energy
