AI4 is an award-winning SME, particularly focusing on Hardware accelerators, and embedded AI optimization. AI4 will further its product offerings to RISC-V-based and AI as a service.

Aitek aims to design and develop a new feature that could be applied by transportation companies and municipalities to manage better transport service, increasing efficiency and reducing costs.

The company expects to integrate measured savings into its City on Cloud platform developed for other EU projects. The end product company supplies a licensed customized Saas cloud module for municipalities and OEMS. BNT will sell the end product as X-as-a-service, Patent/Royalty hiring/selling/ Licensing, and By-subscription fee: business models as described in detail. Additional revenue opportunities will be via consultation services bundled by these services. BTN expects that 20-25% added workforce directly in sales, development and marketing, each year within the company. Indirect impact will be job creation for channel partners and end customers. BTN will submit a workshop paper for Nvidia's annual GTC events and present it in San Jose in the mobility session. BNT also intends to publish min3 max 5 papers in reputable journals (IEEE etc.).

BRNO aims at research activities that will result in scientific output in terms of project presentations, technical reports and publications. Further, the involvement in the project will result in strengthening the education and training provided by BRNO w.r.t. to undergraduate, graduate, and PhD students (in the form of extending existing and providing new courses and providing topics for student projects and these) and professionals (in the form of workshops).

CSIC is a NexTArc consortium partner contributing to the project ecosystem and collaborative research activities.

CUNI is a NexTArc consortium partner contributing to the project ecosystem and collaborative research activities.

Three end products are targeted. 1) A secure Gateway specialised for CAEVs; and 2) HSM for mobility clouds (PRIGM-2 an improved version of our recent general purpose HSM) 3) Dual Redundant Core Security Processor (DCSP) will designed and developed. ERARGE expects significant licensing revenue out of the 3rd offering. The solutions are horizontal and can be extended to all priority areas of CHIPS JU. Among these, our solutions can be promisingly adapted to remote healthcare, smart city, finance and smart grid security in the short term.

ERGTECH will focus on developing solutions in two main areas: i) secure data transmission for in-vehicle and out- vehicle systems, and ii) situational awareness, digital twin of EVs and charging infrastructures. ERGTECH plans to apply these solutions in the automotive domain in close collaboration with OEMs and Tier-I companies. ERGTECH will contact Polish EV manufacturers like Izera, Triggo, Ursus, Solaris, etc. and then extend the scope to the lightweight EV manufacturers. 2-3 conference papers are expected to be submitted to top conferences like IEEE SMC and EUSIPCO in complementary fields including AI-powered smart EV utilization and charging, navigation and smart city applications.

CLEMAP will extend its dynamic load management system from car charging to logistic infrastructure, advancing integration with the grid and mobility. This expansion will secure new market opportunities and establish a prominent position in both the Swiss and European markets. To drive this initiative forward, a dedicated spin-off will be established, explicitly targeting this logistic sector for maximum impact.

Eurotech is a company dedicated to the research, development, production and marketing of miniature computers and high-performance embedded computers. ETH will enhance its offerings of cloud-based loT solutions oriented to support the acquisition of heterogeneous data streams from the sensor to the edge AI server, which will be adopted in the urban mobility use case (smart bus).

GD aims to offer companies interested in eSIM-cards a future-proof lightweight and cost-efficient SIM solution.

HIB aims to broaden the current portfolio of solutions in embedded AI computer vision technologies as well as strengthen its competitiveness in the AI market- being able to develop solutions for the automotive domain. HIB will also increase our expertise in Cyber security in the automotive domain through the improvement of the IMS. Finally, HIB will improve their knowledge of RISC-V architectures, NPUs and other AI accelerators during the implementation of NexTArc results, particularly KI2.2.

IMA aims to extend the component portfolio, competence base and application field for the Automotive development department; results will be analyzed and possibly exploited also by IMA's Industrial and Enterprise Identification systems development department. IMA s.r.o. is a Czech SME established in 1992, specializing in electronic identification, smart cards, RFID/NFC, biometrics and secure digital services. The company has extensive experience in EU-funded R&D projects and standardization activities in healthcare and security domains, including participation in ISO and CEN working groups. IMA develops and integrates advanced solutions for eID, privacy protection, IoT and data processing, with applications in healthcare, automotive, smart buildings and environmental monitoring.

IMEC is a chip manufacturer and provider. In NexTArc it will focus on Low-Power ASIC IP development for smart mobility: NN hardware IPs, peripherals and -optimised hardware solution stack.

LEICOM is taking its expertise in hardware platform development for dynamic load management systems and expanding it to encompass logistic infrastructure. This strategic move will not only deepen the integration between the power grid and the mobility sector but also unlock new market opportunities for LEICOM. By participating in the NEXTArc project, LEICOM is well- positioned to become a prominent player in both the Swiss and European markets. This targeted approach ensures maximum impact and positions LEICOM for continued success.

Research carried out in co-production is central to MDU. This aspect governs all our activities from preparation to the education of 1st year students to our research team. In this regard, CHIPS JU gives a great opportunity to create further synergies. In addition to 2 PhD students, one research assistant 50% will join the team to focus on publications, especially with consortium partners. The total amount of peer-reviewed pubIications wi II be 5 conferences and 3 journal papers during the 3.5 years of project time (2-3 journal papers will be published after the end of the project).

As a pioneering engineering firm, NEP offers an AI platform optimized for machine learning on edge devices. Built upon their unique 'NEP model', this platform facilitates swift transitions from data collection to deployment. NEP's rich history in industrial and medical tech ensures the platform's adaptability and robustness, backed by a collaborative ethos that views clients as partners.

NOM is a technology company specialized in providing information, quantitative analysis, and decision support tools for the planning and management of transportation systems. The solutions it offers are built on three fundamental pillars: big data processing and spatiotemporal data analysis, the development of predictive models based on both machine learning and simulation techniques, and the visualization of information and visual analytics. Through its participation in NexTArc, NOM aims to reaffirm its position as a leader in the development of transportation and mobility solutions based on the fusion and exploitation of massive geolocated data sources. In particular, NOM aims to expand its suite of products by incorporating data from embedded devices in autonomous or connected vehicles for the development of solutions in road safety, environmental monitoring, and traffic and mobility management.

NXPAT aims to achieve the validation of the (RISC-V based power power-embedded AI-enhanced) technology solution ready for further development to achieve a system prototype in 3 years

OTOKAR will integrate the route optimization algorithm into logistics operations inside the factory. As a result of this, the number of forklifts used will be reduced. On the other hand, OTOKAR will develop a positioning algorithm more accurate than the ones in the market by using deep learning algorithms signal fusion techniques etc. A camera based collision avoidance system will also be studied. The positioning algorithm and collision avoidance system can be subject to direct sales. OTOKAR is also aiming to publish min 3 papers in reputable journals.

PLANZER will integrate the route optimisation algorithm between industrial and urban spaces and within urban spaces. PLANZER will develop a dynamic route optimisation algorithm that is usable between spaces but also within urban spaces that not only reduces the logistics burden in traffic but also supports the decision of vehicles and the allocation of specific cargo to specific vehicles. Since PLANZER is well embedded in the logistics scene, they will disseminate the generated knowledge within the scene.

PUMACY will support increasing the efficiency and productivity of automotive business processes while obtaining improved decision-making. As such, the insights gained from the AI empowered data analytics to discover patterns and trends in the data and to make better decisions. A further impact can be to reduce costs of automotive stakeholders through optimizing processes. Particularly, AI on-the-chip solutions can help in this regard by enabling real-time decision-making and reducing the need for expensive human intervention. The use of Embedded AI techniques enhances the safety of vehicles by providing real-time insights into driver behaviour, vehicle performance, and other critical factors.

REDIMI provides a contribution leading to faster and more reliable development of RISC-V architectures in the automotive industry. By realizing the means for data sharing and collaboration among chip developers, a DLT framework combined with a federated machine learning infrastructure can result in better-designed chips with fewer errors. Furthermore, traceability and accountability can be fostered, which can help to build trust among industrial stakeholders, while accelerating the certification and validation processes of the automotive industry.

Silicon Austria Labs GmbH (SAL) is Austria's top research centre for electronics-based systems - they are the technological backbone of digitization. At the Graz, Villach and Linz locations, around 300 employees are currently working on future-oriented solutions for environmental protection, health, energy, mobility and security. In this project, SAL will develop Low-power embedded AI, and AI accelerators solution stack. The project will allow SAL to extend its research in accelerators for RISC-V, towards a distributed/ federated learning setting with security as well as AI blocks. SAL currently plans to make these blocks available under some open licenses. In particular, SAL will contribute to KI2.1 "RISC-V based low power embedded AI-enhanced solution with scalable vector processing and secure distributed learning support for UWB secure ranging and radar applications".

This partner aims to extend its portfolio of software solutions to cover additional services within energy planning in city districts.

SETA is a transport provider in Italy. In this project, we offer a use-case and we intend to optimize smart mobility, and transport solutions with innovation providers. (Evaluation Methodology and Use Case Validation Scenario Specification).

Aims to leverage NexTArc to enable scalable and smart noise mapping platforms for smart cities.

Stream Analyze Sweden AB makes software for interactive analytics on resource-constrained edge devices and lifecycle management of AI/ML models on large fleets of such devices. This far, we have mainly targeted automotive and manufacturing. In NexTArc, we are planning to expand our applicability to include agriculture in our use case collaboration with partners SWECO and SWEG.

Sweco is Europe’s leading architecture and engineering consultancy with 23 000 architects, engineers and other experts to address urbanisation, capture the power of digitalisation, and make our societies more sustainable. In NexTArc Sweco hosts Usecase 1, an Innovation Arena for digital innovation and circular economy that develops through co-creation with local actors in the Stockholm city district Tidningskvarteren where Sweco has its headquarters. A strong interdisciplinary team of architects, planners and digital strategists coordinates partners’ efforts and contributes to the development of a digital twin for circular economy and resource-sharing at neighbourhood scale. Sweco’s interest is to explore circular economy models and how a twin-based work methodology combined with AI agent development may benefit local actors and citizens in ways to both reduce climate impact and support sustainable lifestyles. Sweco is also responsible for Dissemination and Communication (WP9), hereby leveraging on our wide-spread presence and activities across 15 European markets.

SweGreen is a Swedish agtech company, founded in 2019, specializing in in-store farming. We offer automated growing platform to retailers, restaurants and properties for producing premium greens on-site. SweGreen will work on UCl by leading the Demo 1.4 and the AI solutions that will be built in NexTArc will be used to enhance its product offering optimization.

SYSGO GmbH aims to enter into two competitive markets: 1. Automotive Industry (targeting automotive secure gateway aligned with the MIG described in NexTArc) 2. Transportation & Logistics (Edge IoT Devices open issues & challenges such as heterogeneity, optimization, security, data transfer, positioning, etc.)

Research carried out in co-production is central to TALTEC. This aspect governs all our activities from preparation to the education of 1st year students to our research team. In this regard, CHIPS JU gives a great opportunity to create further synergies

Research advancement is the main ambition of UNIMR in NexTArc. UNIMR will use this project to expand and consolidate its knowledge in embedded edge computing HW/SW system co-design, mainly targeting the definition of novel design methodology and novel efficient AI algorithms for edge analytics.

As an academic research institution, innovation is at the very core of UNIPR’s mission. NexTArc will give UNIPR a unique opportunity to expand and strengthen the knowledge of UNIPR in the field of communications with embedded intelligence. This will pave the way to innovative research directions (e.g., AI-based efficient IoT data collection) considering open architectures able to support automotive and logistics applications.

UPM is interested in generating research results applied to industrial processes and contributing to the exploitation dissemination stages from different points of view that consist of presentation of research results within the scientific community, presentation and demonstration at exhibitions, presentation to the general public, communication with academia and industrial clusters and networks. UPM also expects to participate in standardization processes and bodies and in the generation of possible patents with other partners in the consortium to start new market products compliant with the consortium contributions. Research activity done by UPM inside the project will contribute to the generation of lectures, PhD Theses, Master Theses and Final Papers. More specifically, UPM will evaluate the middleware solution's exploitable results to decide the possibility of licensing the use and exploitation to a newly created spin-off company within the future campus program.

ViNotion develops advanced Vision AI and smart camera technologies for real-time image analysis in mobility, industry, and urban environments.

The Zurich University of Applied Sciences (ZHAW) is committed to translating its research into practical applications for industrial processes. They achieve this dissemination through various channels, including presentations within the scientific community, demonstrations at exhibitions, and outreach to the general public. ZHAW actively collaborates with Swiss and international academic institutions, industrial clusters, and networks to ensure maximum impact. Their participation extends to standardization bodies and the generation of potential patents, fostering the creation of new market products aligned with the consortium's goals. Research conducted by ZHAW within the NEXTArc project will contribute to educational materials, Master's theses, and scientific publications. Notably, ZHAW will evaluate the potential of the developed middleware solution for commercialization in collaboration with partner companies. The project also presents an opportunity to strengthen communication between academia and industry by involving international experts throughout the thesis development, evaluation, and assessment phases. Additionally, ZHAW will actively seek alliances with key Swiss and European partners to identify shared goals, promote new strategic industrial research directions within Europe, and facilitate technology transfer. This collaborative effort will position them to compete for new, related projects within the Horizon Europe program.