Workshops series “Novel Enabling Technologies for a Sustainable Future” around the different Technology frameworks facilitated by partner APRE in June, November and December 2024.
Their aim is to develop potential use-cases of sustainable and responsible emerging technologies in the related sector. These co-creation workshops offer an exchange platform for meaningful discussions about the future of sustainable innovation.
The full-fledged co-creation is the third phase of the FORGING value-sensitive innovation journey. Here the broader tech community is involved in the development of use-cases to promote market uptake of responsible technologies.
The event series kicked off last June 2024 in Rome, Italy, where the first two workshops on Artificial Intelligence and Cyber Safe Data Technologies took place.
Each workshop consisted in two main sessions. First, FORGING partners presented the latest achieved results. The technologies identified during the Technology Clustering workshops as most promising from a technical, environmental and societal perspective were presented to the participants.
During the second session, participants have been actively involved in working groups to identify which of the technologies presented could best meet specific human needs thus defining a concrete use-case per technology.
Calendar of upcoming events:
Summary of use-cases resulted from the workshops
Workshop on Artificial Intelligence
USE-CASE 1_DATA-DRIVEN RESILIENT FARMING
Sector: Agrifood
Technology: Abductive reasoning AI
The selected focus was on Agrifood, identifying climate change, heavy regulation, waste management, and crop loss as key issues. The group proposed permaculture-inspired, data-driven resilient farming using modular micro-farms with diverse crops, guided by AI analyzing soil, weather, and disease data. Benefits include democratized food growth, scalable micro-farming, soil regeneration, and improved pest control. Implementing this requires data sharing, pilot projects, new business models in permaculture communities, and adapted regulatory frameworks.
USE-CASE 2_ALICIA – Automated Life Cycle Impact Assessment
Sector: Manufacturing
Technology: Adaptive AI
The group focused on the Manufacturing sector, identifying critical issues such as supply chain resilience, poor working conditions, lack of accountability for externalities, and inadequate data integration. The group proposed a standard Life Cycle Assessment from resource extraction to product retirement, aimed at improving supply chain sustainability, working conditions, and waste management. The solution emphasizes an ethics-driven approach, promote responsible production, reduce waste, reorganize supply chains, and create jobs in auditing, LCA and business modeling.
USE-CASE 3_Data-Driven – Business Model In Manufacturing
Sector: Manufacturing
Technology: Adaptive AI
The group focused on manufacturing, highlighting lack of flexibility as a major issue, affecting resilience to changes and leading to high costs, reduced production, and workforce dissatisfaction.
They proposed using adaptive AI to improve decision-making and resource allocation, benefiting manufacturers with increased efficiency and sustainability. This approach also enhances innovation and growth for the workforce and consumers. Challenges include potential funding shortages, regulatory issues, and resistance to change.
USE-CASE 4_DIA-BEATER
Sector: Health
Technology: Adaptive AI
The group focused on “WELLBEING,” emphasizing prevention, lifestyle choices, and environmental factors. They identified the lack of a wellbeing ecosystem as the main problem, caused by low willpower, intensive agriculture, limited health knowledge, and rapid tech changes. Their solution is a wellbeing ecosystem using AI for adaptive support. They envisage to create “DIA-BEATER,” a tool for high-risk type II diabetes patients, providing tailored support and motivation. Benefits include reduced hospital burden, better mental health, improved preventative care, and healthier lifestyles.
Workshop on Cyber safe data technologies
USE-CASE 1_TRULY – Trustworthy Health Data Access & Share Anytime/Anywhere/by Anyone
Sector: Healthcare
Technology: Zero trust
The group focused on improving healthcare data management, identifying poor data sharing among European providers as a key issue. Causes include outdated processes, resistance to new technology, digital illiteracy, and policy gaps. The solution TRULY uses zero trust technology for a secure, accessible data management system. This would improve reliability, security, inclusivity, and resource efficiency in healthcare, though its energy consumption impact is uncertain.
USE-CASE 2_ ZENCARE (Zero-Knowledge Enhanced Network for Confidential and Reliable Healthcare)
Sector: Healthcare
Technology: Zero Knowledge Proofs + Zero Trust
The group focused on healthcare data protection, identifying inadequate personal data protection/security as the main problem. The solution “ZENCARE” uses Zero Knowledge Proofs and Zero Trust technologies to enhance privacy and security, giving users control over their data. Challenges concern addresses regulatory compliance, technology adoption and IT infrastructure gaps. Benefits imply create a secure, transparent healthcare system, increasing trust and improving services.
GROUP 3_ NEXT GEN P.A.
Sector: Public Administration
Technology: Zero Knowledge Proof
The group identified outdated IT infrastructure, lack of system interoperability, and poor cyber threat awareness in Public Administration as key issues. This leads to personal data being treated as a commodity, resulting in distrust in public administration and more cybersecurity incidents. The solution involves secure distributed data storage, standardized data classification, cyber-aware database naming, and continuous training. They propose an international court for personal data protection to enforce regulations. The impact includes better cybersecurity, enhanced data management, and increased trust in public services. Benefits are seamless public service engagement, greater trust in government, empowered citizens, and environmental gains from digitization.
Workshop on bio-inspired technologies and smart materials
USE-CASE 1_Precision – Forged from Chaos & Unvertainty
Sector: Agrifood
Technology: Bio-inspired sensing technologies, robotics and AI
This group envisaged a solution to improve crop productivity, reduce food waste, and ensure sustainable resource use in the agrifood sector. It is based on precision agriculture, and it entails technologies like bio-inspired sensors, robotics, and AI. This solution aims to benefit farmers through fairer prices, more efficient farming, and reduced environmental impacts. For this reason, it is expected to create both socio-economic and environmental benefits, promoting long-term sustainability. Key challenges include the need for systemic change in education and social acceptance of technology.
USE-CASE 2_ MeTrikot & MeDrikot
Sector: Healthcare
Technology: Organ-on-chip
Focused on the healthcare sector, this group developed a technological solution targeting prevention through user-friendly, early detection wearable devices. These include tattoo-like sensors for continuous monitoring (MeTrikot) and micro-needling devices for targeted monitoring of oxidative stress (MeDrikot), a key health indicator. The solution aims to empower individuals to monitor their health, reduce healthcare costs, and ease the workload of medical staff. Key resources needed are biocompatible materials, funding, and data centers. Potential challenges include data privacy concerns, societal acceptance, and market adaptability.
GROUP 3_ VitriTex
Sector: Manufacturing (Textile industry)
Technology: Bio-engineered bacteria
The group focused on the textile industry with the aim of improving the recyclability of textiles and of enhancing their self-healing properties, to make manufacturing more sustainable. The proposed solution, VitriTex, involves bio-based vitrimers for protective clothing and uses bio-engineered bacteria to break down pollutants and accelerate healing processes. This solution is scalable for other sectors such as energy and healthcare. Key resources needed include biocompatible materials, advanced research facilities, and investment from both public and private sectors.
Workshop on real-time based digital twins & simulation technologies
USE-CASE 1_HATOM-Human Aware Digital Twins Complex Operational Management
Sector: Management (cross-sectoral)
Technology: Cognitive Digital Twins
The group explored solutions for enhancing the management of complex systems in multiple industries, focusing on inefficiencies, resource waste, and weak traceability. Their approach utilizes Cognitive Digital Twins to integrate human knowledge with sensor-based data, enabling better decision-making, sharing of insights, and collaboration across ecosystems. The system provides real-time visual representations of intricate systems, fostering improved efficiency, sustainability, and accountability. Key tools for implementation include AI, sensors, and data infrastructure, while challenges like data upkeep, energy consumption, and privacy concerns remain. The initiative also aims to create more inclusive and improved work environments.
USE-CASE 2_BRIDE- Battery Recycling Innovation through Digital twins re-engineering
Sector: Manufacturing
Technology: Cognitive Digital Twins
The group explored the integration of robotics into the manufacturing sector, specifically aiming to optimize battery recycling for greater efficiency and sustainability. Their solution, BRIDE (Battery Recycling Innovation through Digital-twins re-Engineering), combines robotics with battery data and Cognitive Digital Twins to enhance the disassembly and material recovery processes. This collaboration between humans and machines promotes worker safety and supports circular economy practices for battery materials. With stakeholders including manufacturers, recyclers, and policymakers, the solution is expected to reduce dependency on imported materials, cut carbon emissions, and improve working conditions, with full rollout anticipated in 5-8 years.
USE-CASE 3_TWIN2WIN
Sector: Automative
Technology: Cognitive Digital Twins
The group addressed the need for improved training systems in the automotive industry, particularly for engine assembly workers with varying skills and abilities. Their solution, TWIN2WIN, leverages Cognitive Digital Twins and XR technologies to create a personalized training system that adapts to the individual. This system enhances worker performance and fosters inclusivity, supporting both in-person and remote learning. By minimizing waste and offering broader applications across various sectors, TWIN2WIN promotes a more efficient, sustainable, and inclusive workforce, ensuring that employees are equipped with the skills needed for future manufacturing challenges.
USE-CASE 4_PrevenTwin for WorCares
Sector: Industry
Technology: Cognitive Digital Twins
The group focused on improving safety and working conditions in industrial environments, where high injury rates and poor conditions are prevalent. They proposed PrevenTwin for WorCares, a system utilizing Cognitive Digital Twins for real-time monitoring and predictive risk analysis. By simulating potential hazards, the system offers actionable insights to prevent accidents and improve workplace safety. It aims to foster a healthier, more efficient environment by reducing injuries, enhancing morale, and ensuring sustainable resource use. Key stakeholders involved include workers, safety officers, and technology providers, with the ultimate goal of transforming workplace safety through data-driven solutions.
Workshop on human centric solutions & human machine interaction
USE-CASE 1_SEAMLESS- Social Environment, Adaptative, Multiple modalities Low-x Ergonomics for Safety and Sustainability
Sector: Manufacturing
Technology: Natural Language Processing
The group tackled the challenge of enhancing human-machine collaboration in manufacturing, addressing issues such as low-cost labour, slow robotic assembly, and monotonous tasks. Their solution, SEAMLESS, proposes a shift to a more integrated human-machine system that includes ergonomic enhancements and personalized digital twins. By utilizing adaptive robotics, natural language processing, sensors, and haptics, it aims to improve worker engagement, safety, and skill development. The technology, which could take 5 to 20 years to deploy, aligns with SDGs and aims to reduce costs and boost worker satisfaction.
USE-CASE 2_TECHCARE
Sector: Healthcare
Technology: Digital Twins + Internet of Things + AI
The group focused on improving the well-being and decision-making processes for caregivers and care recipients, especially in high-stress eldercare settings. Their solution, TECHCARE, combines real-time data analytics with decision-making protocols to make care more efficient and empathetic. Using technologies such as Digital Twins, AI, and IoT, the approach seeks to improve care quality, reduce stress for caregivers, and ensure privacy and safety. Targeting caregivers, families, and care providers, it aims to optimize resources, support well-being, and address ethical issues in caregiving.
USE-CASE 3_You’ll Never Fly Alone
Sector: Aviation
Technology: Natural Language Processing + Internet of Things
The group worked on improving communication and situational awareness in high-stakes environments such as aviation and healthcare. They introduced “You’ll Never Fly Alone,” a multisensory support system powered by natural language processing, aimed at improving operational communication for pilots. The system leverages IoT, sensors, signal processing, and AI to aid protocol execution and enhance decision-making. While it presents cybersecurity risks and environmental challenges, its goal is to improve safety, streamline operations, and optimize decision-making in aviation and other safety-critical areas.
USE-CASE 4_AIMS – Aircraft Intelligent Maintenance System
Sector: Aviation
Technology: Digital Twins + Internet of Things
The group identified inefficiencies in the complex and costly process of aircraft maintenance due to a lack of automation and technological integration. Their solution, AIMS (Aircraft Intelligent Maintenance System), integrates IoT and Digital Twins for predictive maintenance, aiming to reduce downtime, improve safety, and streamline operations. The system is designed to enhance working conditions for operators and reduce maintenance costs. It also promotes sustainability by increasing component reuse and reducing waste, although challenges like investment costs and resistance to adopting new technologies remain.
