Financováno: Horizon Europe Framework Programme (HORIZON) 
Výzva: HORIZON-WIDERA-2023-ERA-01 
Číslo projektu: 101131728 
Zahájení projektu: 1. Ledna 2024 
Doba trvání projektu: 36 měsíců 

.

Mise

Hlavním cílem projektu BEAGLE je objevovat nové inovativní trhy a hodnotové řetězce prostřednictvím strategií zaměřených na identifikaci nových tržních příležitostí. Projekt usiluje o udržitelný ekonomický růst a konkurenceschopnost.
 

Inovativní metodologie

BEAGLE zavádí průkopnický přístup založený na strategii modrých oceánů, který podporuje vytváření nových trhů a inovací.

 

Spolupráce napříč sektory

BEAGLE propojuje akademické instituce, výzkumná centra a průmyslové klastrové sítě. Tento přístup podporuje partnerství a sdílení znalostí napříč sektory, čímž posiluje inovace a společné cíle. Prioritami SCHP ČR v rámci projektu jsou obnovitelné energie a přeměna odpadního CO2

 

Strategické cíle

  • Identifikace 12 nových tematických mezer na trhu
  • Návrh 20 inovačních projektů s konkrétními realizačními plány
  • Konsolidace nových tematických mezer na trhu k přilákání investorů.
     

 

Strategie „modrých oceánů“

Strategie „modrých oceánů“ projektu BEAGLE se zaměřuje na identifikaci nových trhů, kde neexistuje konkurence, namísto soupeření na přeplněných trzích („červené oceány“). Klíčovými prvky této strategie je identifikace nevyužitých příležitostí, eliminace nadbytečných nákladů a zvýšení hodnoty pro zákazníky i firmy. Tento přístup podporuje kreativitu, diferenciaci a udržitelnou konkurenceschopnost. Výsledkem je prostředí, kde mohou organizace dosahovat vysoké konkurenceschopnosti a zisku.

 

Více informací naleznete na webu projektu BEAGLE zde
 

Výzva Open Call #1

První výzva programu BEAGLE hledá 120 odborníků z průmyslu, kteří se zapojí do identifikace tržních příležitostí a inovací v uvedených oblastech. Účastníci připraví video-podklady, které budou následně využity k zapojení akademických inovátorů v navazující výzvě Open Call #2.

Pro zájemce z řad odborné veřejnosti je k dispozici odkaz na webinář na Youtube, ve kterém je detailně popsána nejen výzva Open Call#1, ale i možnost zapojení do projektu Beagle.

Video je k dispozici zde.

 

Více informací naleznete zde.

Proč se zúčastnit?

Účast na programu BEAGLE vám přinese:

  • Mentoring od zkušených odborníků pro rozvoj vašich nápadů.
  • Praktickou spolupráci s týmy BEAGLE.
  • Podporu udržitelnosti projektů.
  • Aplikace strategie „modré oceány“ pro vlastní využití.

 

Důležité termíny

  • Vyhlášení výzvy OC#1 je 29. listopadu 2024
  • Uzávěrka přihlášek je 28. února 2025 (do 17:00 CET)
  • Webinář proběhne 11. prosince 2024 v 9:00 CET (záznam je k dispozici zde)

 

Více informací naleznete na webu projektu BEAGLE zde.

Činnosti BEAGLE podporované SCHP ČR

Svaz chemického průmyslu ČR se účastní zejména následujících projektových aktivit:

  • mapování osvědčených postupů v oblasti zhodnocování znalostí (technologické inovace nebo postup hodnocení příležitostí)
  • účast na náboru 30 expertů pro účast v projektu v rámci „Open call #1, #2“ a posilování vazeb mezi akademickou obcí a průmyslem
  • spolupráce na přípravě a výběru 20 inovačních projektů s konkrétními plány realizace a motivací investorů
  • účast ve smíšených pracovních týmech (průmysl a akademie) se zaměřením na obnovitelné energie, analýzu spotřeby energie, decentralizované obnovitelné energie, přeměnu odpadního CO2 a cirkulární zemědělství a obaly.
  • spolupráce při šíření (diseminaci) informací o projektu prostřednictvím webu SCHP ČR, nebo na sociálních sítích a v rámci členské základny prostřednictvím pracovních skupin a výborů svazu
  • Zajištění zpracování plánu a činnosti monitorování, replikace a maximalizace dopadů.
     

Realizace projektu: leden 2024–prosinec 2026

Realizace projektu předpokládá zapojení projektového týmu a vybraných expertů z řad členských společností svazu, pracovních skupin a národních technologických platforem v souladu s rozsahem a mírou zapojení SCHP ČR.

Přehled 12 klíčových tematických mezer na trhu projektu BEAGLE

SCHP ČR se zapojil do práce expertních smíšených týmů a rozvoji inovačních nápadů v 5 z 12 tematických tržních mezer.

MT #1: Renewable Energy Combined with AI

 

The Renewable Energy with artificial intelligence (AI) market niche involves the integration of AI technologies into renewable energy sectors, such as solar, wind, hydro, and bioenergy, to enhance efficiency, predictability, and scalability. The Renewable Energy with AI niche is suitable for innovation, driven by the urgent need for sustainable energy solutions and the growing pressure to reduce environmental impact. By addressing specific customer needs and industry challenges, AI-powered renewable energy technologies offer significant potential to optimize operations, minimize costs, and foster environmentally responsible energy practices. Additionally, this niche will leverage AI to address critical challenges within renewable energy systems, such as energy variability, equipment maintenance, grid integration, and data management, enabling cleaner, more reliable, and cost-effective energy solutions. As global demand for sustainable energy sources continues to grow, AI applications within the renewable energy sector have the potential to unlock innovative solutions that improve operational performance and environmental sustainability.

  1. Key Needs and Opportunities
  • Accurate Energy Forecasting: AI models help predict renewable energy production based on weather and usage patterns, allowing utilities to better balance supply and demand, thus minimizing waste and improving reliability.
  • Optimized Maintenance for Equipment Longevity: Predictive maintenance using AI can monitor equipment health (e.g., turbines, solar panels) to anticipate and prevent failures, reducing downtime and operational costs.
  • Grid Integration and Load Balancing: AI-powered solutions enable seamless integration of renewable energy into the grid, dynamically adjusting loads to prevent overloading and underutilization, thus enhancing grid resilience.
  • Energy Storage Optimization: AI supports efficient energy storage and discharge management, allowing energy providers to store excess renewable energy during low-demand periods and release it when demand is high.
  • Real-time Data Analytics and Decision Support: Access to actionable data and insights allows energy producers and operators to make informed decisions, enhancing productivity and sustainability.
  • Cost Reduction and ROI Improvement: AI helps reduce operational costs of renewable energy systems while maximizing output, thus improving return on investment (ROI).
  1. Potential Customers

 

This niche will target the following group of customers: 1) Utility Companies and Energy Providers. 2) Renewable Energy Plant Operators. 3) Smart Grid Operators. 4) Industrial Energy Consumers. 5) Energy Storage Companies. Government and Regulatory Bodies.

MT #2: AI-Enhanced Cybersecurity

 

AI-Enhanced Cybersecurity is a specialized market niche that leverages artificial intelligence (AI) to protect digital systems, networks, and data from an ever-growing array of cyber threats. By incorporating AI technologies, this niche focuses on creating advanced, proactive security solutions that can identify, analyze, and respond to threats in real-time. Traditional cybersecurity methods often struggle to keep up with the speed and complexity of modern cyber-attacks, which are increasingly automated and sophisticated. AI-enhanced cybersecurity addresses these challenges by enabling adaptive, intelligent defenses capable of evolving alongside emerging threats. This market niche presents significant potential for innovation, as companies look for more effective ways to secure their networks and data in response to increasing cyber threats.

  1. Key Needs and Opportunities

 

  • Real-time Threat Detection and Response: AI enables systems to analyze large volumes of data in real-time, identifying anomalies and suspicious activities that could indicate potential threats.
  • Automated Incident Response: By automating responses to specific types of attacks, AI can minimize response times, contain incidents, and reduce damage, helping security teams manage threats faster and more efficiently.
  • Behavioral Analysis and User Authentication: AI can analyze user behavior to detect unusual patterns, flagging potential unauthorized access or insider threats. Advanced user authentication can strengthen identity verification and prevent credential misuse.
  • Advanced Malware and Phishing Detection: AI algorithms can analyze email content, attachments, and URLs to identify phishing attempts and malware that evade traditional signature-based detection.
  • Network Traffic Monitoring and Anomaly Detection: AI continuously monitors network traffic to detect unusual patterns that might indicate a cyber-attack, helping companies prevent data breaches and minimize attack impacts.
  • Predictive Analysis and Threat Intelligence: AI helps organizations anticipate emerging threats based on global cyber-attack patterns, enabling preemptive defenses that reduce vulnerability to new attack vectors.

 

  1. Potential Customers

 

This niche will target the following group of customers: 1) Large Enterprises and Corporations. 2) Government and Public Sector. 3) Telecommunication and IoT Companies. 4) Cloud Service Providers and Data Centers.

MT #3: Personalized Health Care

 

Personalized health care is an overarching framework for proactive, personalized healthcare that provides individuals with a personal health plan to maximize their health and minimize disease. Personalized health care is an approach that applies the concepts of systems biology to medicine and is personalized, predictive, preventive, and participatory (so called P4 medicine).  Personalized or precision medicine initiatives seek to enhance medical interventions by leveraging various data types, including biological information and biomarkers. It utilizes predictive technologies to establish each individual’s health risks and facilitates patients’ engagement in their health along with the development of plans and a care delivery system designed to achieve the best health outcomes. Personalized health care is based on the established principle that each individual is born with unique biological characteristics based on their genetic inheritance. Thanks to access to individual's current clinical status and subsequent possibility of evaluation of their risks of disease it is possible to entirely change the approach to health care. This new approach deviates from the original focus on identifying and responding to disease to more sophisticated strategic approach whereby disease risks are quantified and, where possible, prevented by strategic planning. This new approach termed, “personalized health care,” is based on the scientific foundation of systems medicine that recognizes the dynamic relationship between genetic inheritance, environmental exposures, and systems biology. There are a number of challenges associated with personalized medicines, especially with respect to obtaining their approval for routine use from various regulatory agencies. In addition, there are many issues associated with the broad acceptance of personalized medicines on the part of different health care stakeholders, such as physicians, health care executives, insurance companies, and, ultimately, patients. Almost all of these challenges revolve around a need to prove that personalized medicine strategies simply outperform traditional medicine strategies, especially since many tailored or personalized therapies can be very expensive. There exist convincing strategies that proved that personalized medicine protocols and strategies could outperform traditional medicine protocols and strategies. Despite the progress in personalized medicine there are still challenges associated with personalized disease prevention, personalized health monitoring, and personalized treatment of overt disease. In fact, there are emerging and next-generation personalized medicine strategies that attract attention of scientists. These strategies include the use of patient-derived cell and organoid ‘avatars’ for determining the best suitable therapies for that patient, the use of intense individualized diagnostic and monitoring protocols to detect signs of disease, the development of personalized digital therapeutics, and the use of personalized medicine approaches in treating patients with fertility issues. There are many benefits of the application of this approach especially in terms of medical benefits or health outcomes. Basically, it deals with improved outcomes in the areas of prevention, diagnosis, treatment and palliation of chronic and non-chronic diseases, and expanded understanding of determinants of health, social and economic impacts as economic opportunities, health system efficiencies, human capital gains, and well-being and other social benefits and eventually better function of the health systems.

 

Miroslav Špaček on behalf of MT#3

UWB, Pilsen

MT #4 - AI-Powered Credit Risk Assessment: Maher Asal (HV)

 

Abstract

The financial industry faces mounting challenges in enhancing credit risk assessment practices, particularly in terms of transparency, fairness, and alignment with sustainability objectives. Traditional credit risk models predominantly rely on historical financial data, which often restricts adaptability in a dynamic market. Additionally, AI-based credit models, despite their promise, encounter criticism for opacity and potential biases that can lead to unfair lending practices. Moreover, there is an increasing demand to integrate Environmental, Social, and Governance (ESG) metrics into credit assessments to better reflect long-term sustainability risks.

This paper examines the potential of the AI-Driven Transparent Credit Risk Assessment Platform (AICRA) as a transformative solution to these challenges. AICRA leverages Explainable AI (XAI) to ensure interpretability in credit decisions, a real-time bias detection module to enhance fairness, and ESG risk integration to provide a dual risk assessment framework. By combining these features, AICRA aims to deliver a modern credit assessment model that aligns with regulatory expectations and the ethical standards of responsible finance. The study employs a phased methodology, encompassing platform development, pilot testing with selected financial institutions, and full rollout to a broader market. Data from pilot implementations will be analyzed to assess AICRA’s effectiveness in improving transparency, reducing bias, and incorporating ESG factors into the risk evaluation process. Expected results suggest that AICRA will enhance trust and compliance in credit assessments, giving financial institutions a competitive edge through responsible lending practices. This research contributes to the evolving field of AI in finance by offering an adaptable, transparent, and ethically grounded credit assessment framework that supports the industry's transition toward sustainable finance

MT #5 - Drone Delivery Services 

 

Urban Air Mobility (UAM) is becoming a key topic to provide new mobility services and new connections and modes of transport in urban environments. The concept is increasingly present in cities´ plans for a sustainable development and economic growth. Several initiatives and projects have been developed in recent years or are currently underway with the goal to build the U-SPACE framework and test the operations that will allow UAM solutions to run safely and coordinated. 

 

The use of unmanned aerial vehicles (UAVs) or "drones" are expected to affect significantly the logistics sector in the following decade. So far, the use of drones was utilized by the logistics sector for undertaking operations related to inventory management, inspection and surveillance. Given though the rise of the e-commerce by 30% during COVID and the constantly increasing demand for next-hour deliveries, drones have started being noticed by the city logistics market as the means for achieving faster, cheaper and more efficient deliveries However, still, there are certain challenges and limitations in the wide deployment of UAVs in urban delivery service operations such as technological limitations for covering effectively a wide spectrum of delivery needs in terms of speed and capacity caring requirements, legal limitations for setting a safe and secure ground of their implementation and facilitating higher penetration levels and finally societal limitations referring to the need for higher levels of public acceptance. 

 

The opportunities of drone delivery services are versatility and might transform various industries by improving efficiency, reducing costs and enhancing accessibility, among others: retail and e-commerce (from groceries to electronics), healthcare (medical supplies, vaccines, blood, and lab samples to underserved areas), food (quick delivery avoiding traffic as well as open delivery services for underserved peri-urban areas), agriculture (seeds, fertilizers and pesticides directly to farms), disaster relief (deliver food, water and medical aid in inaccessible areas) and logistics and warehousing (transport goods within large facilities or between nearby locations). 

 

 

MT #6 - AI-Powered Energy Consumption Analysis: Laurent Vautier (NEXTMOVE)

 

Energy efficiency is one of the cornerstones of the European Union’s strategy to achieve its ambitious climate goals, including carbon neutrality by 2050. For companies, optimizing energy consumption is a critical step toward reducing greenhouse gas emissions, lowering costs, and increasing competitiveness. Artificial Intelligence (AI) offers unprecedented opportunities to revolutionize the way energy is analysed, managed, and optimized.

AI-powered energy consumption analysis relies on advanced algorithms and machine learning techniques to collect, process, and interpret vast amounts of energy usage data in real-time. By leveraging predictive analytics, these tools can forecast energy demand, identify inefficiencies, and recommend tailored solutions to reduce consumption. AI systems are also capable of detecting anomalies, such as equipment malfunctions or unexpected energy spikes, enabling companies to address issues proactively and minimize waste.

Beyond operational optimization, AI-based solutions can integrate external factors such as weather conditions, energy market prices, and regulatory constraints to guide strategic decision-making. These systems help companies adapt to dynamic energy environments, balance energy consumption with renewable energy sources, and even participate in energy trading platforms for additional savings.

While the benefits of AI-powered energy management are significant, implementation challenges remain. These include the high initial investment costs, data privacy and cybersecurity concerns, and the need for skilled personnel to manage and interpret AI-driven insights. However, successful examples of AI adoption in energy management from industrial facilities to smart buildings demonstrate its potential to drive a sustainable and efficient energy transition for businesses of all sizes.

 

MT #7 - Sustainable mobility hubs

 

The European Union has committed itself to reduce by 55% greenhouse gas emissions. To that end, the transition of mobility towards new uses with low GGE plays a key role, by encouraging soft mobility, including the use of public transportation.

Sustainable mobility hubs can be a part of this transition for urban mobility. They can be considered as the counterpart of MaaS, capable of making interconnections between transports modes, in an increasingly complex picture of urban mobility. Mobility hubs represent a flexible concept and they are diversly implemented.

As a physical connection point proposing a multimodal offer, these hubs gather and connect the various travel solutions in the city and around: walking, cycling, shared mobility, on-demand transport, public transportation, etc. They can include carpool and carsharing options, real-time information and ticket selling for public transportation, biking rental and infrastructure (repair station/shop, parking, etc.), scooter rental, micro warehouses for last-mile delivery, charging point for electric mobility but also other kinds of services as parcels storage and delivery.

It is expected that these hubs offer efficient mobility alternatives, participate in the unblock of the traffic, the reduction pressure on parking spaces and widely the attractiveness of the city.

If several hubs are already implemented, particularly in Nord and Eastern Europe, various challenges still exist: business and governance model, user experience, ticketing/digital dimension (MaaS), services to implement and to ensure the high quality service, consideration of the needs against situations, etc.  

Examples: Mobipunt, Hvv Switch, Jelbi Station, etc.

 

MT #8: Decentralized Renewable Energy (DRE)

 

The global shift towards sustainable energy has heightened the importance of decentralised renewable energy (DRE) systems. Unlike traditional centralised power models, DRE solutions generate energy near the point of use, utilising local resources such as solar, wind, biomass, and geothermal energy. This approach enhances energy efficiency, promotes energy independence, and stimulates community-based economic development.

Traditional centralised energy grids often face challenges like inefficiency, high transmission losses, and vulnerability to disruptions. Many rural and underserved areas lack reliable access to electricity, and current energy systems struggle to integrate renewable sources effectively at the community level. Flexible, sustainable energy solutions are essential to address these issues.

DRE systems tackle these challenges by building energy networks tailored to local communities. Key features include:

  • Microgrid Infrastructure: Combining various renewable energy sources to provide reliable and efficient power with integrated storage options.
  • Smart Energy Management: Utilizing intelligent technologies to monitor and manage energy consumption in real-time, maximising efficiency and reducing waste.
  • Community Involvement: Engaging local stakeholders in the planning and managing of energy systems to enhance ownership, economic opportunities, and social equity.

The DRE market is expected to grow rapidly as countries commit to reducing carbon emissions and securing stable energy supplies. Governments and investors increasingly support these systems due to their potential to revolutionise energy access worldwide, from rural villages to major urban areas.

Why DRE Systems Stand Out:

  • Reliability: Providing a steady energy supply with reduced risk of widespread outages, even in emergencies or disasters.
  • Environmental Impact: Utilizing local renewable resources decreases fossil fuel dependence and protects the environment.
  • Economic Benefits: Creating jobs and business opportunities within communities, driving local economic growth.

Decentralised renewable energy systems open new market opportunities where industry and academic research can collaborate. By connecting businesses and researchers, we can drive innovation and create practical, sustainable energy solutions that benefit everyone.

MT #9: Farm-to-Fork Supply Chains (F2F)

 

The demand for sustainable and transparent food systems has made farm-to-fork (F2F) supply chains more essential than ever. Unlike traditional food supply chains, which are often inefficient and lack transparency, F2F systems focus on delivering food from farms to consumers in the most direct, efficient, and environmentally friendly manner. This approach enhances local food security, reduces waste, and supports sustainable agricultural practices.

Traditional food supply chains can be wasteful, disconnected, and difficult for consumers to trust. Consumers increasingly seek information about the origins of their food and assurance of sustainable production practices. Simultaneously, farmers need better access to markets and fair compensation. Transparent and efficient food supply solutions are necessary to address these challenges.

F2F systems address these issues by creating clear and direct links between producers and consumers. Key features include:

  • Digital Traceability: Implementing blockchain to provide transparency throughout the food journey, building consumer trust.
  • Efficient Logistics: Utilizing data-driven logistics systems to reduce food waste and minimise transportation emissions, making the supply chain more sustainable.
  • Local Sourcing and Distribution: Emphasizing local and regional supply chains to support nearby farmers and reduce environmental impact.

The F2F market is growing as consumers demand more sustainable and transparent food options. Governments and investors also support these systems, recognising their potential to improve food security and reduce environmental impact.

Why F2F Systems Stand Out:

  • Transparency: Digital tools enable consumers to trace the origin of their food, building trust and loyalty.
  • Waste Reduction: Smarter logistics reduce food waste and enhance supply chain efficiency.
  • Local Impact: Supporting local farmers and producers strengthens regional economies and reduces the carbon footprint.

By connecting research with real-world applications, we can drive innovation and spread sustainable food practices, benefiting people and the planet.

MT #10: CO2 as a source for Circular economy

 

The European Union places great emphasis on the circular economy as a key part of its strategy for sustainable development and decarbonisation. In terms of decarbonisation, this means creating a cycle of CO2 capture, subsequent use and re-capture. Few idustrial sectore are potential user: food industry, transport, chemical industry, constrution etc. (see picture below).

 

P2X (Power to Methane, Power to Methanol) via CO2 utilisation is one of the prefered option.

 

 

                                      CO2 as a source of carbon for „green hydrocarbons“production

Carbon and hydrogen on a renewable basis should bring new solutions in an ecologically acceptable (when being economically attractive) future carbon-neutral production practice. The development in the area of ​​cheaper H2 production should be complemented by sophisticated CCS and CCU processes and thus complete effective circulating production processes.

MT #11: AI & IoT for Smart Cities

 

As cities face increasing pressures for sustainability, efficiency, and livability, integrating AI and IoT technologies presents innovative opportunities to transform urban environments. These intelligent technologies enhance real-time monitoring, optimise resource management, and improve infrastructure resilience.

 

IoT sensors deployed throughout the city gather extensive data on various factors, including air quality, traffic flow, and energy consumption. AI algorithms then analyse this data to support dynamic decision-making. For example, AI-powered traffic systems can help reduce congestion and lower emissions, while smart grids ensure efficient energy distribution.

 

The convergence of AI and IoT creates a connected ecosystem and provides city managers and residents with actionable insights that promote a greener, smarter, and more inclusive urban environment. However, implementing these systems on a large scale comes with complex challenges, including ensuring data privacy, achieving interoperability, managing infrastructure upgrades, and gaining public trust.

 

AI and IoT can significantly contribute to developing resilient and sustainable cities worldwide by addressing these challenges.

MT #12: Circular Agriculture and Packaging

 

The circular economy reshapes traditional practices in the agrifood, packaging, and connected sectors by establishing a closed-loop system that significantly minimises waste and environmental impact. This innovative approach capitalises on resource recovery, turning waste and by-products into valuable resources throughout the supply chain.

 

The focus is on sustainable resource utilisation, where agricultural by-products are creatively repurposed, and packaging materials are derived from renewable, biodegradable sources. In this transformation from “waste” to “valuable resource,” biorefineries are crucial, as they convert agricultural residues and other biological materials into value-added, bio-based products such as biofuels, bioplastics, and natural chemicals.

 

Packaging materials are now sourced from renewable, biodegradable resources, reinforcing a sustainable resource cycle. Additionally, intelligent and active packaging solutions extend product shelf life, enhance food safety, and improve resource efficiency. IT-enabled traceability systems enhance logistics transparency, enabling consumers and producers to track products from farm to table, ensuring quality and safety.

 

This approach is essential for reducing greenhouse gas emissions, supporting global climate goals, and promoting responsible consumption patterns, ultimately contributing to more sustainable and resilient food systems.

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