Projets Européens IG-RV

Maud Marchal, 09-07-2022.

HORIZON-CL4-2023-HUMAN-01-21: Next Generation eXtended Reality (RIA)

Expected Outcome: Projects are expected to contribute to the following outcomes:

• Next generation of XR devices and applications, by exploiting cross fertilisation between technologies such as 5G/6G, IoT, data, artificial intelligence, edge and cloud computing, and microelectronics but also across domains of use such as (but not limited to education, manufacturing, health, cultural heritage, media and security).

• More realistic, more affordable and gender-neutral devices and applications, developed by European companies, respecting European values of ethics, privacy, security and safety, aiming at technological sovereignty and resilience.

Scope: The following two types of research and innovation proposals are expected:

i. The development and integration of advanced XR hardware components, such as displays, optics and sensors, for a new generation of XR devices providing greater visual, wearable, vestibular and social comfort. Special relevance should be given (a) to technological breakthroughs in photonics and new materials aiming to increase the image quality and to reduce the size and weight of XR devices; (b) to displays and optical elements bringing the capabilities of XR devices closer to those of the human vision; (c) to more efficient architectures for enhanced performance, reduced power consumption and improved heat dissipation; (d) to novel systems that cater to the widest range of users, including those that need prescription correction; (e) to advanced optical- and photo-detector technologies for sensing systems, including sensing data processing; (f) to innovative XR connectivity components supporting the demanding requirements on latency, data rates and resilience; and (g) to novel materials with tailored optical, mechanical and processing properties for a tight integration of subcomponents, enabling overall miniaturization and environmentally sustainable mass-production of future XR devices.

At least one proposal of this type will be funded.

i. The development of new solutions aiming to improve the user experience, skills and capacity in social and professional XR setups. This includes tools and services for the creation and management of interactive virtual worlds and 3D models, realistic full body avatars and intelligent agents. The solutions will also seek to enhance the interoperability, performance and accessibility of XR experiences. The proposals will include prototypes validated in realistic scenarios, proving how innovative the developed solutions are, how they exploit synergies between disciplines and domains, and how far beyond state of the art they go.

At least one proposal of this type will be funded.

The Commission considers that proposals with an overall duration of typically 36 months would allow these outcomes to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other durations.

This topic requires the effective contribution of SSH disciplines and the involvement of SSH experts, institutions as well as the inclusion of relevant SSH expertise, in order to produce meaningful and significant effects enhancing the societal impact of the related research activities

HORIZON-CL4-2023-HUMAN-01-22: eXtended Reality for Industry 5.0 (IA)

Expected Outcome: Projects are expected to contribute to the following outcomes:

• Develop “XR made in Europe”, contributing to technological sovereignty.

• Contribute to develop virtual worlds European platforms.

• Support the use of XR technologies for a sustainable, human-centric and resilient European industry¹.

Scope: The following two types of innovation proposals are expected.

• i. The development of XR applications to support companies in all industrial ecosystems, especially SMEs, to use innovative interactive and immersive technologies, increasing their competitiveness, productivity, efficiency and human-centricity. The applications should be robust, gender-neutral safe and trustworthy, especially in terms of cybersecurity, privacy and health issues. Proposals should exploit cross fertilisation between academics, industry representatives and end-users around well thought-out scenarios. Moreover, proposals should include activities to showcase the results, widely disseminating and exploiting the outcomes.

• ii. The creation of a European reference platform aiming to develop and prototype advanced interoperable XR solutions to solve common challenges encountered by the industry (in areas such as assembly, maintenance, remote operation, training, design, logistics, etc.), placing the wellbeing of workers at the centre of the production process. The platform will be populated with third party-projects exploring a wide range of XR technologies and taking benefit of other emerging technologies (such as 5G/6G, IoT, data, artificial intelligence, edge and cloud computing, and microelectronics). In order to facilitate the integration with existing IT systems and policies, the EU XR platform for industry should prioritize XR content, tools and solutions based on open standards, such as OpenXR and WebXR. The solutions provided by the platform should aim to cover as many industry ecosystems as possible. Involvement of end-users is essential in defining specifications and testing.

At least one proposal will be funded for the innovation type i.

Only one proposal will be funded for innovation type ii.

Financial support to third parties

The type ii innovation action will provide financial support third-party projects from outstanding XR innovators, SMEs and other multidisciplinary actors through a minimum of three open calls during the lifetime of the project.

The consortium will define a coherent and coordinated programme logic for the third-party projects, offering the necessary technical support, coaching and mentoring, to ensure a significant advancement and impact in the innovation domain, including in terms of interoperability and standardisation. These tasks cannot be implemented using the budget earmarked for the financial support to third parties.

Proposals should make explicit the intervention logic for the area and their potential to attract relevant top XR talents and to deliver a solid value-added to the third-party projects. Proposals should also prove the expertise and capacity of the consortium in managing the full life-cycle of the open calls transparently and efficiently.

As support and mobilising of XR innovators is key to the type ii IA of this topic, a minimum of 60% of the total requested EU contribution should be allocated to financial support to the third parties.

The Commission considers that proposals with an overall duration of typically 36 months would allow these outcomes to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other durations.

For ensuring focused effort, third parties in type ii will be funded through projects typically in the EUR 250 000 to 500 000 range per project, with indicative duration of 12 to 15 months.

This topic requires the effective contribution of SSH disciplines and the involvement of SSH experts, institutions as well as the inclusion of relevant SSH expertise, in order to produce meaningful and significant effects enhancing the societal impact of the related research activities.

HORIZON-CL4-2023-HUMAN-01-05: Through AI from Disinformation to Trust (IA)

Expected Outcome: Proposal results are expected to contribute to one of the following expected outcomes:

• Innovative AI solutions for trusted information production for media professionals.

Innovative AI solutions for supporting trustworthy online activity of citizens.

Scope: Following the results of the first HE work programme, the second work programme will support innovation activities to move closer to AI-based market and ultimately widely available solutions that can play an important role in ensuring pluralistic access to meaningful information, quality content and trustworthy online interaction. This topic is fully in line with both the EDAP – European Democracy Action Plan and MAAP – Media and Audiovisual Action Plan, for reinforcing the European media ecosystem and maintaining resilient democratic systems, in times of crises and of need for adaptation and change.

Given the emergence of the next generation of social media as part of digital universe(s) or fediverse(s), which are more immersive and based on virtual realities and gaming contexts, the detection of different forms of content manipulation (e.g. deep-fakes, tampered content and scammed environments) becomes even more challenging. Solutions provided would include the correlation/comparison of various sources of information, multi-modal language interpretation, rapid visual pattern detection in moving images and simulated environments, capabilities as recommendation engine/personal companion, and interfacing with augmented, virtual reality and gaming environments. Solutions should be gender-sensitive and not perpetuate harmful stereotypes. The innovation actions will bring together technological providers, media professionals and end users for ensuring market readiness of the results.

Proposals should clearly identify the expected outcome it will focus on (i.e. media professionals or citizens). All proposals are expected to embed mechanisms to assess and demonstrate progress (with qualitative and quantitative KPIs, demonstrators, benchmarking and progress monitoring), and share communicable results with the European R&D community, through the AI-on-demand platform. Activities are expected to achieve TRL6-7 by the end of the project.

All proposals are expected to allocate tasks to cohesion activities with the other subtopic, the PPP on AI, Data and Robotics and funded actions related to this partnership, and to extend and apply the results from the previous research and innovation topic on AI against Disinformation.

HORIZON-CL4-2023-HUMAN-01-82: Art-driven digital innovation: Towards human compatible and ecologically conscious technology (CSA)

Expected Outcome: This call encourages a mind change regarding the role of the arts in R&I in the spirit of a European innovation policy based on culture and values. It is building on results of the S|T|ARTS program that has demonstrated concrete benefits of art-technology collaboration for digital innovation and uptake of digital in society and economy.

1. a. Facilitate artistic experimentation with (digital) technologies to accelerate development and novel use cases of digital technologies. The emphasise will be on ecologically conscious and human compatible technologies and use case of technologies.

To this end, the consortium will fund (via FSTP in form of grants) S|T|ARTS residencies of artists to be hosted by EC funded projects, technology institutions, or SMEs/industrial actors (both digital providers and end-users of digital). In the spirit of the topic, hosts of residencies must provide access to technology free of cost. The consortium will mentor residencies and help in follow-up/exploitation of the outcomes (commercial or other). Non-exclusive examples of intended outcomes include:

• Art-driven development and use of Artificial Intelligence (AI) in spirit of the EC communication on ‘Trustworthy AI’

• Art-driven applications of high-performance computing (visualisation, simulation etc).

• Art as a catalyst for uptake of the digital in society and economy in the spirit of digital innovation hubs.

• Art-driven use of technology to facilitate the Green Transition, in the spirt of the ‘New European Bauhaus’ (urban development, green manufacturing, circular economy, etc.)

• Art-driven use of digital media to fight disinformation, for example to promote factual narratives and change behavior in context of Green Transition and climate change.

  a. Continuation of the annual S|T|ARTS prize: Achieve visibility of successful art and technology collaborations via an annual prize (FSTP in form of prizes) in two categories - to be defined by proposers, organize annual calls (launch, evaluation) and disseminate the prizes and its winners in an award ceremony and an exhibition.

  b. Organise an annual S|T|ARTS Festival. The festival will highlight synergies of digital – in particular AI - with human creativity in art and music. Artistic use of digital can push limits of digital technology and is considered a measure of compatibility of digital with human values and needs.

Scope: While Europe is strongly pushing innovation based on technological and scientific progress, it has always put social and ecological priorities on the same level as economic growth. This has led to a new alliance of the arts with S&T as part of a European innovation policy rooted in values and culture. Artists become key drivers of ‘art-driven innovation’ towards ecologically conscious and human compatible technologies. In this spirit, DG CONNECT launched S|T|ARTS - innovation at the nexus of Science, Technology and the ARTS – and the European Commission president proposed the ‘New European Bauhaus’, where synergies between art and novel technologies are identified as enablers of the Green Transition. The present call will thus encourage actors in R&I to adopt artistic experimentation as a complementary method of technology development and use across all of the EC programs.

The Commission considers a duration of 36 months as appropriate.

HORIZON-CL4-2024-HUMAN-01-02: Collaborative intelligence – combining the best of machine and human (AI Data and Robotics Partnership)

Expected Outcome: Projects are expected to contribute to the following outcomes:

• Advancement of human-machine interaction - general advancements in human-computer interaction, operational for a broad range of AI-reasoning systems and applicable to a broad range of application areas of AI.

• Improved human decision-making and analytic abilities - Demonstrate that collaborative decision-making improves over human decision-making and that the collaborative decisions cover all stages of reasoning (that they are based on an improved coverage of data and knowledge sources, on an improved analytic ability to reason from input to output, and on a well-communicated decision).

• Demonstrate the value of collaborative decision making by improved effectiveness, efficiency, completeness, limits of knowledge indication and other objective or quantifiable subjective measures.

Scope: The R&I priorities require work at different levels, including both foundational research and well-studied piloting efforts, concentrated in impactful projects, bringing critical mass of expertise and investment to demonstrate potential for more than one major application sectors respectively.

Research should focus on:

• foundational research towards the next generation of collaborative AI, bringing excellence, critical mass and novel approaches as well as quantitatively proven improvement in the levels of human-machine collaboration.

• simulations and experimentation (with and without humans in the loop) to explore the consequences of different interventions and/or to explore the design approaches that help manage decision making.

• integrating advances from [effective, efficient, anticipative, multi-modal] human-computer interaction and from [incremental, continually learned, or anticipative], automatic reasoning systems in order to create new generations of collaborative AI-systems that better and more naturally serve human needs. The means of collaboration can cover the whole range of multi-modal stimuli: lingual, image, video, sound and other forms of interaction, whatever is arguably the most appropriate in the interaction process.

Multidisciplinary research activities should address all of the following:

• Proposals should involve appropriate expertise in Social Sciences and Humanities (SSH)

• Research should build on existing standards or contribute to standardisation. Interoperability for data sharing should be addressed.

• Projects should build on or seek collaboration with existing projects and develop synergies with other relevant European, national or regional initiatives, funding programmes and platforms.

• Contribute to making AI and robotics solutions meet the requirements of Trustworthy AI, based on the respect of the ethical principles, the fundamental rights including critical aspects such as robustness, safety, reliability, in line with the European

Approach to AI. Ethics principles needs to be adopted from early stages of development and design.

All proposals are expected to embed mechanisms to assess and demonstrate progress (with qualitative and quantitative KPIs, benchmarking and progress monitoring, as well as illustrative application use-cases demonstrating concrete potential added value), and share communicable results with the European R&D community, through the AI-on-demand platform or Digital Industrial Platform for Robotics, public community resources, to maximise re-use of results, either by developers, or for uptake, and optimise efficiency of funding; enhancing the European AI, Data and Robotics ecosystem through the sharing of results and best practice.

HORIZON-CL2-2023-HERITAGE-ECCCH-01-02: A European Collaborative Cloud for Cultural Heritage – Innovative tools for digitising cultural heritage objects

Expected Outcome: Projects should contribute to all of the following expected outcomes:

• Cultural heritage professionals in Europe, including curators, conservators and researchers of cultural heritage, use a common set of new innovative tools and methods for the digitisation and visualisation of cultural heritage objects (3D and enhanced 2D) with regard to their visible and non-visible properties and characteristics, which are accessible through and connected to the European Collaborative Cloud for Cultural Heritage (ECCCH).

• The European Collaborative Cloud for Cultural Heritage (ECCCH) provides cultural heritage institutions and professionals with enhanced technological and methodological capabilities to study cultural heritage objects, to share related data of their visible and non-visible properties and characteristics, and to develop new forms of collaboration.

Scope: This topic aims at designing and implementing innovative tools and methods for digitisation of (a) visible characteristics and (b) non-visible characteristics of cultural heritage objects, to be incorporated into the European Collaborative Cloud for Cultural Heritage (ECCCH).

As regards digitisation of visible characteristics of cultural heritage objects, technologies are now satisfying the needs for a considerable part of uses and objects. For instance, in the field of digital documentation of cultural heritage, three-dimensional acquisition and reconstruction methods have been developed in the past twenty years, using photogrammetry and laser scanning techniques to capture the characteristics of physical cultural heritage objects. Such methods already provide robust solutions for the digital reconstruction of the geometry and visual appearance of object surfaces. In addition to these methods, in the field of cultural heritage conservation various non-destructive testing (NDT) techniques have become important technical and scientific means of examination. Such techniques allow understanding the phenomena of deterioration and defining the restoration, conservation and documentation needs of cultural heritage objects.

Nevertheless, there are still major needs in cultural heritage that require further research and innovation on more advanced digitisation tools and methods:

• New AI-powered tools and methods that improve the digitisation process of tangible cultural heritage objects. The robustness and efficiency of the 3D digitisation process should be improved, especially in the case of massive digitisation (for example collections of objects). The accuracy and completeness of surface appearance acquisition should also be improved, as well as the mapping of complex reflectance data on digital surfaces. Furthermore, such solutions should yield new improved methods for post-processing and cleaning of the 3D models produced.

• Improved methods for acquiring and processing enhanced 2D representations (e.g. reflectance transformation imaging, multispectral, panoramic), and for better integrating 2D representations with 3D representations.

• Future 3D models need to encode other key attributes in addition to the usual geometric and reflectance data, such as local uncertainty information. New tools and methods are therefore needed to calculate and encode local accuracy limits with high precision in reconstructed 3D models. These tools should be capable of producing measurement-based limits of the similarity between the digital model and the physical object at any surface point, as well as algorithmically estimated accuracy boundaries.

• To model a complex assembly is a costly effort, and today often requires dismounting the assembly - which is often not possible. Specific digitisation solutions should be developed that are capable of mixing various digitisation approaches (e.g. scanning and computer tomography scans) in order to capture dynamic or hidden characteristics of complex assemblies without dismounting them.²

As regards the study of non-visible characteristics of complex objects, nowadays different techniques are used, e.g. multispectral imaging, X-rays, infrared reflectance, terahertz imaging, etc. Proposals should focus on innovations at the data acquisition level, with a view to improve the quality and usability of the data generated. An important aspect is the robustness, reliability as well as the ease of use of any tool and method for analysing the visible characteristics and non-visible materials properties of cultural heritage objects under real world conditions. In addition, several recent experimental approaches have shown that multimodal analysis techniques should include a temporal dimension, observing the evolution of features and phenomena over time.

These challenges highlight the need for flexible, transferable, and simple solutions for documenting multimodal analyses. These solutions should include the integration of data acquisitions from different technologies into complex data structures that provide new analysis opportunities for conservation scientists, conservators and curators. This requires the introduction of new visualisation tools that act as virtual environments for scientific exploration, allowing scientists and curators to explore the full material complexity of cultural heritage objects beyond what is visible.

Large datasets are often generated (e.g., many dozens of images in the case of hyperspectral imaging). To address this, new AI solutions should be developed to generate classified or pre-analysed data, enabling the selection and/or identification of specific elements, images or regions of interest that exhibit important differences for subsequent analysis and validation by the human expert.

The tools and methods introduced should focus on geometric and projective consistency of heterogeneous data from different technologies, with respect to different scales of observation and analysis, over a wide spectral range, to produce an integrated digital representation. Spatially localised characterisation of individual material layers is one of the goals, including coupling multi- or hyperspectral analyses with physicochemical characterisation of materials. New methods for access, exploration, and temporal monitoring of acquired data should be developed, including their interactive visualisation and classification.

The proposed software tools and methods to be developed should go beyond the lab prototype status, should be practical and possible to deploy easily in un-controlled environments (e.g. digitise in a museum room), and should ensure low cost and flexibility of use. The component for data integration into the ECCCH may extend the features of the basic tool developed by the project funded under topic HORIZON-CL2-2023-HERITAGE-ECCCH-01-01, with the goal of streamlining the upload of metadata/paradata and of raw sampled data.

The proposals should demonstrate the potential of the developed tools and methods through representative case studies, conducted in collaboration with relevant stakeholders. These case studies should cover a significant share of the range of cultural heritage objects, materials and conservation/restoration issues. The results of these case studies should produce emblematic data that can serve as models for promoting the re-use of the tool(s) and methods in other contexts and by other users within the ECCCH.

The proposed tool(s) to be developed should be implemented adopting the low-level libraries established by the project funded under topic HORIZON-CL2-2023-HERITAGE-ECCCH-01-01. The tool(s) developed should be compliant with the design of the ECCCH, and should be integrated with the ECCCH before the end of the project, together with proper documentation. All software and other related deliverables should be compliant with the data model and the software development guidelines elaborated by the project funded under topic ‘HORIZON-CL2-2023-HERITAGE-ECCCH-01-01’.

The proposals should furthermore make provisions to actively participate in the common activities of ECCCH initiative. In particular, the proposals should coordinate technical work with other selected projects and contribute to the activities of the project funded under the topic HORIZON-CL2-2023-HERITAGE-ECCCH-01-01.

The proposals should set up its project website under the common ECCCH website, managed by the project funded under topic HORIZON-CL2-2023-HERITAGE-ECCCH-01-01. The proposal is further expected to include a budget for the attendance to regular joint coordination meetings and may consider to cover the costs of any other joint activities without the prerequisite to detail concrete joint activities at this stage.

HORIZON-CL2-2024-TRANSFORMATIONS-01-06: Beyond the horizon: A human-friendly deployment of artificial intelligence and related technologies

Expected Outcome: Projects should contribute to all of the following expected outcomes:

• Established guiding principles based on human rights and European values on how to approach long term future opportunities and challenges posed by artificial intelligence and related technologies.

• Structurally enhanced capacities to foresee, evaluate and manage the long term opportunities and challenges associated with artificial intelligence and related technologies.

• Well founded and prioritised recommendations for European policy on R&I and in other key areas aimed at :

  • Ensuring that Europe is prepared to exploit the opportunities for the benefit of citizens and society, and at the same time face the challenges raised by potential developments and deployments of artificial intelligence and related technologies based on science and evidence as well as human rights and European values, and

  • Reinforcing Europe’s capacity to guide the development and deployment of these technologies in ways aligned to human rights and European values.

Scope: The history of “artificial intelligence” technologies (AI) is marked by great optimism and expectation, sometimes followed by disappointment. However, we have recently seen a sustained upsurge in interest and the successful uptake and application of AI in a variety of significant areas such as drug discovery, autonomous vehicles, social media, industrial robotics, and logistics, to name a few. We have witnessed significant successes in the development and deployment of machine learning, particularly for tasks normally associated with human perception³. We have also seen significant successes in symbolic and logic-driven AI for problems that require reasoning about constraints, automated reasoning, planning, etc.⁴ AI has had significant impact in the arts and humanities, and AI-based methods and tools are becoming more widely used in the cultural arena.⁵

Nevertheless, today the collection of computer technologies commonly labelled artificial intelligence, along with related technologies for instance in the fields of data science, neuroscience and biotechnology, already show the potential to disrupt and impact the rights of individuals and the wellbeing of societal structures. For example, there have been many documented case studies where AI-based applications have exhibited undesired gender and racial bias⁶. AI systems have been (mis-)used to micro-target and influence voters in elections as well as in the creation and dissemination of disinformation⁷, and otherwise impact on human agency and autonomy. Many ethical issues arise in the development of AI systems, such as their use in medical devices, brain-computer interfaces, reasoning about human mental and emotion state, etc.⁸

Concerns are often raised that AI technologies may imply major societal disruptions such as massive job displacements due to the increasing use of AI-drive automation and robotics, while research show that AI can also help filling gaps in workforce⁹¹⁰.

In 2018, the European Commission established the High Level Expert Group on Artificial Intelligence (HLEG-AI), which was tasked with developing a set of ethics guidelines for Europe that would help ensure that AI systems be human-centric and trustworthy. The importance of a human-centric approach to AI has been a cornerstone of EU policy-making in the field for several years and is the clearly articulated position of the EU. The European Commission published a pioneering draft AI Act in April 2021, the first legal framework on AI in Europe, which addresses the potential risks of using AI¹¹. The Horizon Europe work programme under Cluster 4 is funding related research and innovation actions under the header ‘Leadership in AI based on trust’.

The common principle across all of these EU initiatives are seven key requirements for trustworthy AI¹², as proposed by the HLEG-AI and adopted by the European Commission, as well as the importance of protecting the fundamental rights of individuals¹³.

Against this backdrop, before being faced with a ‘fait-accompli’ in terms of potentially undesirable influence of AI on the European society and economy and to make sure that all the beneficial potential of AI deployment is fully realised, we should anticipate and prepare for possible and high impact scenarios.

The proposal should cover all the following aspects:

• Decisive contributions to develop a sound European capacity building on the long term human and societal implications of AI, building, as appropriate, on previous work of the HLEG-AI, ADRA¹⁴, or other relevant European and national AI initiatives.

• A solid scientific approach, providing an in-depth analysis of successful existing deployment of AI and the impact they have on European economy and society. Such analysis should also significantly contribute to awareness raising of such deployments, providing a reality check of capabilities/benefits, but also limitations of current AI solutions, and how the latter are currently addressed.

• Scenario based analysis of future long term potential benefits to citizens and societies, as well as an analysis of related challenges and threats.

• Based on this, proposals should elaborate a set of guiding principles, ensuring a broad support and appropriate involvement of other relevant AI initiatives.

• Proposals need to take a multi-disciplinary and cross-sectorial approach, and engage with a wide set of stakeholders, including research organisations, enterprises, citizens¹⁵, policymakers, public private partnerships such as the AI, Data and Robotics Partnership, and other relevant EU projects and initiatives around AI.

• European policy actions should be proposed in a priority order, notably in the area of research and innovation but not excluding other important policy areas, that would serve to strengthen European preparedness and resilience in the face of future developments within AI and related emerging technologies as well as to guide the development and deployment of these technologies in a desirable direction.

Proposals should build on existing knowledge, activities and networks, such as the HLEG-AI and other initiatives funded by the European Union. Funded proposals should also take into account existing EU policy in the area, such as Excellence and trust in artificial intelligence under A Europe fit for the digital age¹⁶. Furthermore, the proposals should seek synergies with closely related actions, such as relevant R&I actions funded by Horizon Europe or Horizon 2020¹⁷.

HORIZON-CL5-2024-D4-02-02: Robotics and other automated solutions for assembly, renovation and maintenance in a sustainable built environment (Built4People Partnership)

Expected Outcome: Project results are expected to contribute to all of the following expected outcomes:

• Reduction of construction and renovation time on-site (at least 40% reduction).

• Reduction of errors in construction and renovation works.

• Improved resource efficiency.

• Reduction of construction and renovation costs.

• Reduction of greenhouse gas emissions resulting from, and improved energy efficiency of the works on-site.

• Reduced environmental impact of construction works, including pollution, particulate matter¹⁸ and noise, in the immediate vicinity.

• Reduction of waste generated from the works on-site.

Scope: The transformation of the built environment should take place in a way that minimises the environmental impact of the works themselves. With the increasing rollout of highly energy efficient, sustainable buildings and deep renovation, there is a growing need for the development of robotic and automated solutions to support sustainable building construction, renovation and maintenance processes that are less disruptive, cleaner and faster.

Proposals are expected to address all of the following:

• Investigate the use of robotic systems (including those used for 3D printing) and automation for construction and deep renovation, in order to reduce time of construction and renovation works, reduce construction errors, as well as facilitate maintenance, also minimising the impact of the works on the surrounding built environment.

• Explore the potential for lower construction costs through automation and robotics resulting from increased speed, improved resource efficiency and avoidance of errors.

• Develop robotic and automated design and construction techniques that increase energy efficiency and reduce greenhouse gas emissions from construction and renovation works on-site.

• Develop approaches that use digitally assisted design to improve resource efficiency and safety, reduce waste, and reduce construction time.

• Investigate the use of automated technologies for surveying, inspection and monitoring of the site.

• Investigate the use of automated support to augment workers’ capability and safety (e.g., lift robots, exoskeletons, automated construction site monitoring, use of augmented and virtual reality).

• Test and validate the prototyped solutions in at least three prototypes to assess the proposed approaches for a variety of buildings typologies representative of the European building stock. These prototypes should be validated in a lab or another relevant environment. The testing and validation are expected to address both new construction and renovation.

• Contribute to the activities of the Built4People partners and to the Built4People network of innovation clusters.

This topic implements the co-programmed European Partnership on ‘People-centric sustainable built environment’ (Built4People). As such, projects resulting from this topic will be expected to report on results to the European Partnership ‘People-centric sustainable built environment’ (Built4People) in support of the monitoring of its KPIs.

HORIZON-CL6-2024-GOVERNANCE: Enhancing working conditions and strengthening the work force through digital and data technologies – the potential of robotics and augmented reality in agriculture

Expected outcome:

In line with the farm to fork strategy, the Common Agricultural Policy post 2022, and the Headline ambition of a Digital Age, a successful proposal will contribute to transition to a fair, healthy and resilient agriculture. It will therefore also directly and/ or indirectly contribute to the enhancement of the sustainability performance of the sector, including social sustainability, and competitiveness in agriculture through research and innovation which will support the further deployment of digital and data technologies as key enablers.

Project results are expected to contribute to all of the following expected outcomes:

• Enhanced working conditions in agriculture (including increased safety of workers and reduced drudgery) through innovative digital solutions exploiting the potential of augmented reality.

• Lowered environmental impacts and productions costs and increased product quality in and through the use of digital technologies, through robotics and augmented reality in particular.

• Reduced the share of risky or unattractive actions/tasks to be performed by workers through automation-base solutions.

• Mitigated lack/ shortage of work force in agriculture in some through automation-based solutions.

Scope:

Digital and data technologies can facilitate the work in agriculture, enhance working conditions¹⁹ and mitigate the challenge of a lack of work force, by which some branches and regions are affected. They have the potential of making farm-related jobs more attractive, including for younger generations, and to make them safer. Digital and data technologies can increase the effectiveness and efficiency of applications, including for instance through a higher level of precision, and thus increase the sustainability and competitiveness of the sector. Automation is increasingly used in agriculture; frequently, the cost-effectiveness of innovative digital and data technologies still presents a bottleneck to their use in the sector, particular in fields where their application is not primarily relevant for increasing process efficiency and effective. Technical solutions based on augmented reality approaches offer many opportunities to facilitate and enhance the use of digital technologies in agriculture, to enhance the performance of digital tools, and to provide remote assistance, which is important for remote businesses.

Proposals should address the following:

• Development of augmented-reality based solutions to improve working conditions, safety and failure avoidance, and to further increase robotic performance.

• Development of robotic solutions to improve unhealthy working conditions, where applicable. Robotics tasks to be fostered might be directly related to agricultural production, such as harvesting, weeding, crop monitoring, animal husbandry or indirectly related, such as logistics/ farm management.

• Development of robotic solutions for tasks, for which there is a high interest/ need to support and/ or replace the human work force, not only because of an interest to improve productivity, but to ensure production in an environmentally and socially sustainable way.

• Strengthening AI capabilities for agro-robotics in the fields of applications fostered by the proposals including through the use of (scalable) platforms to further increase robotics performance.

• Development of business models for the use of the developed innovative technologies under consideration of various farm structures and inter-farm linkages as well as of various biogeographic and socio-economic framing conditions.

• Development of a tool for system analyses of the consequences for farmers and rural communities of enhancing working conditions through automation and augmented reality and of replacing human work force with robotic systems.

The development of such technologies should take into account relevant (forthcoming) legislation, in particular linked to the horizontal Act on AI, the Liability Directive, and Machinery Directive/ Regulation. Projects are encouraged - when reflecting on the effects of automation and augmented reality - to dedicate particular attention to youth/ younger generation, women and persons with disabilities as well as to the affordability of digital solutions. Projects are expected to develop training material allowing the targeted end users and multipliers to easily deploy and promote the new technologies.

Proposals must implement the ‘multi-actor approach’ including a range of actors to ensure that knowledge and needs from various stakeholder groups, including farmers, farm workers, farm advisors and scientists are taken into consideration. This topic should involve the effective contribution of social sciences and humanities (SSH) disciplines.

Projects are expected to take into consideration the results of other related Horizon 2020/ Europe projects as well as of other relevant EU-funded projects and initiatives.
Proposals may involve financial support to third parties, e.g. to academic researchers, hi-tech start-ups, SMEs, and other multidisciplinary actors, to, for instance, develop, test or validate developed approaches, tools and applications or to provide other contributions to achieve the project objectives. A maximum of € 60 000 per third party might be granted. Conditions for third parties support are set out in Part B of the General Annexes. Consortia need to define the selection process of organisations, for which financial support may be granted. Maximum 20% of the EU funding can be allocated to this purpose. The financial support to third parties can only be provided in the form of grants.