AIoT*5G – Artificial intelligence, edge computing and IoT solutions in distributed systems
Team: Alejandro Noé Díaz Vargas, Margus Rohtla, Ahmed Hassan Helmy Mohamed, Aleksei Fjodorov, Mihkel Tommingas, Juri Kubinets, Larissa Joonas, Muhammad Mahtab Alam, Indur Ait, Alar Kuusik, Frederick Rang, Yannick Le Moullec, Natalja Ivleva
Time: 2023 - 2029
The project aims to create and test Industrial Internet of Things (IoT and IIoT) solutions with a focus on energy-efficient industrial data acquisition and the application of machine learning to IoT devices in the field. In addition, the project addresses the problem of secure and reliable IoT data transmission through the development of 5G and beyond private mobile network technologies. The project also explores resources to make IIoT devices developed under the project more environmentally friendly in the future by improving the recyclability of their components.
Sustainable Artificial Internet of Things (SAIoT)
Team: Alar Kuusik, Levent Aksoy, Aivar Usk, Masoud Daneshtalab, Allan Niidu, Mohammad Hasan Ahmadilivani, Marko Koort, Yannick Le Moullec, Tamás Pardy, Jakob Rostovski, Indur Ait, Anet Tammets, Jürgen Soom, Vahur Kampus
Time: 2024 - 2028
The project focuses are the development and implementation of sustainable, i.e. energy-efficient, environmentally friendly and secure Artificial intelligent Internet of Things (AIoT) software and hardware technologies based on machine learning at the edge, hybrid microelectronics combining analog and digital technologies. Piloting applicability of the R&D results in the case of future electronic and other sustainable materials aimed at reuse and for the monitoring of such materials.
Uninterrupted 5G Coverage Across Via Baltica Corridor
Team: Yannick Le Moullec, Anet Tammets, Muhammad Mahtab Alam, Osama Mohamed Mostafa Elgarhy
Time: 2025 - 2027
Boosting TalTech Capacity in Reliable and Efficient AI-Chip Design.
Team: Masoud Daneshtalab, Peeter Ellervee, Artur Jutman, Yannick Le Moullec, Tara Ghasempouri, Maksim Jenihhin, Jaan Raik, Levent Aksoy
Time: 2024 - 2027
Boosting TalTech Capacity in Reliable and Efficient AI-Chip Design
Team: Tara Ghasempouri, Masoud Daneshtalab, Peeter Ellervee, Artur Jutman, Jaan Raik, Maksim Jenihhin, Yannick Le Moullec, Levent Aksoy
Time: 2024 - 2027
Building on TalTech’s expertise in the field of computer engineering and its high-level capacity in the domain of diagnostics and testing of nanoelectronic systems, this project aims at establishing in TalTech, with the strong support of the Advanced Partners, the capacity to R&D&I a complete customised AI-chip design flow. The research ambition of the TAICHIP (TalTech AI-chip) action is a leading-edge forward-thinking R&D framework for reliable and resource-efficient custom AI-chips based on open HW architectures (e.g., RISC-V, NVDLA), open EDA (Electronic Design Automation) tools, methodologies and implementation technologies satisfying the requirements of AI applications of tomorrow. TAICHIP project also allows building at TalTech the necessary scientific knowledge, research skills, administrative and management skills, as well as strengthening its advanced training and education capacity. Evenly related to the central goal are the additional measures that focus on building the supporting capacities, as well as dissemination, exploitation and communication, and public policy focused activities.
Secure 5G-Enabled Twin Transition for Europe’s TIMBER Industry Sector
Team: Aamir Latif, Henri Schasmin, Tauno Otto, Alar Kuusik, Simone Luca Pizzagalli, Anet Tammets, Ivo Müürsepp, Anet Tammets, Henri Rammul, Anum Umer, Indur Ait, Yannick Le Moullec, Kashif Mahmood, Yevhen Bondarenko, Muhammad Mahtab Alam, Vladimir Kuts, Kärt Kängsepp
Time: 2022 - 2025
5G-TIMBER project aims to validate through robust evidence the latest 5G Industrial Private Network features and standards specifications for Wood Value Chain (WVC) under realistic conditions. In particular, to conduct advanced field trials of the more representative and innovative data-driven material, production and installation flows that implicate manufacturing across 4 prominent industries in the wood sector including, machinery and wood house elements manufacturing, construction and renovation towards green buildings, wood waste valorisation, and established telecom SME industries in a project remit that spans 3 representative European regions (Norway, Estonia, Finland). The project incentivises the opportunistic uptake of 5G in real-life business conditions. Specifically, 5G- TIMBER will target to increase wood-based materials recycling by 50%, increase manufacturing productivity by 15%, reach 99% of the work done in the factory (vs. 85% today), reduce on-site work by 10%, reduce product nonconformities by 10%, and increase the safety of workers in wooden houses production and onsite assembling. Validation of above overall targets through >100 interdisciplinary innovation driven technical, business and service-level KPIs for 09 diverse WVC usecases across 3 categories i.e., data driven sawmill woodworking machines; modular wood-house factory; construction and renovation with wooden elements, valorisation of composite waste. Usecases will be incrementally validated by 2 lab trials followed by 2 field trials in iterative cycle covering significant portions of end-to-end WVC. 5G-TIMBER also includes a comprehensive business case and exploitation strategy that incorporates novel approaches to materializing the value of data produced in industrial environments based upon 4 distinct business models. Our 16-partner consortium is driven by strong industrial and SME partners, renowned organisations the majority of which participate in FoF cPPP, 5G-PPP, GD projects.