Ongoing Projects
There has been a fast development of new technological devices to monitor glucose levels, matching the ubiquitous dissemination of digital connectivity and social networking. The increase in social, educational, and age disparities among patients, more information on the web and social networks, and the development of better technological devices created a new environment characterized by several challenges. Unfortunately, the ecosystem for treating patients within this new reality has not changed, and there is a need to develop a better understanding of the real value generated by technologies in terms of the patient's behaviors and their decision processes to achieve higher levels of patient empowerment for Type1 and Type 2 diabetes prevention since they have related to different methods of risk perception. These challenges highlight the need to estimate the value offered to each patient by technology to achieve patient empowerment for more efficient prevention. NEODIPPE is born to pursue a crystal clear mission: to explore and identify the best use of technological developments to empower patients to prevent and treat diabetes, which implies innovating the traditional paradigms of health services from occasional appointments to networking monitoring and empowerment, supporting the processes of decision making and proposing new approaches to clinical practices, health organizations, and public financing in terms of the latest needs, resources, and preferences of the patients.
More information from: ETIS
The overall objective of the 5G-BALTICS project is to deploy 5G infrastructure for the transport corridor to reach uninterrupted coverage that meets service requirements for Connected and Automated Mobility (CAM), Intelligent Transport Systems (ITS), and also for multi-service/multi-application 5G services along the European transport corridor via-BALTICA. The project covers the transport corridors in Estonia, Latvia, and Lithuania including the cross-border sections, and provides 663km of 5G uninterrupted coverage from Tallinn to Kalvarija. The project has multiple cross-border segments, as the deployed sites will enable 5G coverage in Estonia, Latvia, and Lithuania, while special focus activities will be undertaken for uninterrupted coverage at the border crossing.
The PROTECT project aims to develop techniques for identifying drones piloted via cellular networks. Two scenarios are considered: cooperative and uncooperative networks. In the collaborative scenario, the cellular network is leveraged for drone detection while in the other case, passive radar techniques are utilized through common broadcast signals. The project will tackle the identification and incapacitation of drone swarms as well as single drones, developing and experimentally evaluating AI algorithms. This project’s outcomes will greatly interest stakeholders ranging from security and defense to law enforcement and public safety, particularly for mobile network operators.
More information from: ETIS
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.
The goal is to study new solutions & principles for electrical impedance spectroscopy (EIS) with significantly improved metrological and functional characteristics, like higher measurement accuracy, resolution and speed, lower power consumption and wider frequency and dynamic ranges. New solutions enhance the existing and enable new applications of EIS in healthcare, biology and industries. The principles & solutions to measure biological & physiological properties of organs, tissues and microorganisms/pathogens, as well as of composites, alloys etc. are the subjects of the research. Unique low-cost low-power miniaturized high-resolution and flexible measurement components with various connectivity (IoT, BAN etc) will be created by new EIS groundings. An important R&D aspect is synchronous signal processing and communication in EIS sensor-arrays. Research aspects: sampling theory AI/ML) and metrology (eg novel calibration techniques, methods of implementation in biology and medicine.
More information from: ETIS
The general goal is the development of electronic devices for clinical measurement of soft tissues. Specific result is a device for continuous monitoring of the condition of the heart muscle during heart surgery. Heart disease is the most common cause of death (WHO 2019, https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death). Surgery plays an important role in the treatment of advanced heart diseases, with a risk of damage to the muscle (of a stopped heart!) during surgery. Current heart protection methods are poorly controlled, as based on schemes developed by trial and error. The unique solution being created will ensure the real-time usage of protective solutions based on objective heart muscle indicators. The technology being created, also allows measuring of various other muscle, fat and connective tissues, and could also distinguish benign and malignant tissues. The solutions created use inventive electrical impedance spectroscopy technologies of TalTech.
More information from: ETIS
The importance of antimicrobial membranes has significantly grown during the recent COVID pandemic era. Nanofibrous antimicrobial membranes have seen novel applications in biomedicine, such as face masks against viral threats or wound dressings used in chronic patient care. Composite electrospun nanofiber meshes are convenient to use as antimicrobial membranes. At present, the lack of automated, inline quality control limits both the pilot and large scale production of multi-material multilayer composite membranes. The alternative, manual re-calibration greatly limits production throughput and thus commercial viability. The goal of this R&D activity is to create technology for scalable inline quality control of electrospun nanofiber meshes. Using cognitive electronics, the system will be capable of continuous multiparameter monitoring and electrospinning process control to maintain optimal product quality and distribution.
More information from: ETIS
Silicon-based CMOS technology is approaching its performance limits, but the demand for more powerful computers — driven by rapid advances in applications such as the Internet of Things, big data and artificial intelligence (AI) — remains. The discovery of various nanomaterials provides new opportunities to further develop information processing technology. Carbon nanotubes (CNTs) have, in particular, demonstrated excellent properties as a channel material in transistors. Computers based on CNT field-effect transistors (FETs) have been theoretically predicted to provide a power-performance improvement of ten times over computers based on Si-CMOS technology. However, the fabrication of high-performance CNT-nanoelectronics, and the realization of the full potential of CNTs, is highly challenging. A technological revolution would be a reliable approach to fabricate a new family of CNT-based devices that could enable aligned arrangement of the nanotubes avoiding the critical steps related to nanolithography. In particular, biofabrication using DNA-templated CNT arrays FETs has been demonstrated to further scale the alignment of CNTs within the FETs well beyond standard lithographic feasibility. 3D-BRICKS will raise this concept of integrated self-assembly CNT-nanocircuits to a completely new level by moving towards the third dimension. Indeed, the versatility of DNA nanotechnology will be the root for conceiving 3-dimensional (3D) CNT-FETs and CNT-nonvolatile memories. DNA nanotechnology will also enable to complement the CNT deposition with metallic connections, hence realizing a working circuit. This will reduce the foot-print of the final device while enhancing its efficiency, hence providing a breakthrough solution to realize the next-generation nanoelectronics. Our approach will enable the production of scalable biotemplated electronics that can be extended to multiple applications such as metamaterials, sensors, optoelectronics, and others.
More information from: ETIS
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.
More information from: ETIS
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.
More information from: ETIS
Finished Projects
5G-ROUTES is a 5G-PPP Phase 3 project whose aim is to validate through robust evidence the latest 5G features and 3GPP specifications (R.16 & R.17) of CAM under realistic conditions. In particular, it will conduct advanced large-scale field trials of most representative CAM applications to demonstrate seamless functionality across a prominent 5G cross-border corridor (Via Baltica-North), traversing Latvia, Estonia and Finland. This will help to boost confidence and accelerate the deployment of 5G-based interoperable CAM ecosystems and services throughout Europe. It also aims at validating 5G as a true enabler of innovative CAM services that cannot be realised by today’s technology. Specifically, 5G-ROUTES will provide: (a) validation of >150 network, business and service-level KPIs for 13 diverse CAM use cases that require 5G performance capabilities, covering several V2X scenarios in automated cooperative, awareness and sensing driving. 5G-ROUTES also focuses on uninterrupted infotainment passenger services on the go and multimodal services in the context of complete connectivity-enabled ecosystems around passengers and cargo over 3 different modes of transport (vehicles, rails and maritime); (b) innovative AIbased technological enablers for facilitating the execution of the field trials. Several scenarios will be considered for each use case covering cross-border, cross-telecom operators, cross telco-vendors, integrated cross terrestrial-satellite and cross-transport-mode settings. These will be incrementally validated, starting from lab trials, followed by localised large-scale trials at strategic cross-border locations (Valga city, Tallinn & Gulf of Finland) and finally in larger-scale trials covering significant portions of transport routes along the selected corridor. Our 22-partner consortium is driven by industry heavyweights and renowned organisations the majority of which participate in 30 out of 63 5G-PPP projects and in several 5G-PPP Working Groups.
The availability of 5G infrastructure in transport corridors is an important step in promoting sustainable mobility, developing innovation in transport, and freight transport logistics, and improving road safety. Furthermore, ensuring the continuity of services both within the transport corridors of Via Baltica and Rail Baltica and across national borders is an essential precondition for the successful digitalization and development of the road. Within the project, a study will be carried out, containing technical solutions and financial model(s) for the needed 5G deployment infrastructure of the transport corridors of Via Baltica and Rail Baltica, capable of cross-border 5G services in the Baltic States.
New or reoccurring bacterial threats are a major challenge of this century, and a delayed response due to the lack of field-testing options risks human lives and causing an epidemic. Classical microbiology techniques are relatively slow, while cytometric methods allow the measurement of cell count, morphology etc. in an easy, reliable, and fast way. State of the art flow cytometers are high-throughput benchtop instruments that are neither portable nor cheap enough for field testing, causing logistic delays in bacterial testing in remote areas and conflict zones or where infrastructure is limited. The goal of this R&D activity is to create the proof of concept of and develop the methodology for low-cost, fully portable flow cytometers based on droplet microfluidics, which will not only allow field analysis of bacteria, but will have a single-cell resolution. Furthermore, through cognitive electronics, the system will be easy to use and fully automated from sample input to result output.
Worldwide, 2 million neural disease patients may benefit from functional electrical stimulation. Existing wearable assistive actuators (e.g. neuromuscular stimulators) lack context and situational awareness, and thus increase the patients’ safety risks and reduce their quality of life. We propose an innovative closed-loop wireless communication system that adds i) intelligent monitoring, ii) automated neuromuscular stimulation, iii) feedback from the actuator-to-coordinator for tuning and decision-making. We will: -investigate and select the suitable emerging wireless communication technology that meets the time-critical application requirements -propose novel coexistence strategies to avoid congestion and achieve higher throughput -develop task sharing and scheduling solutions to meet the time, energy, and reliability constraints -Implement, test and validate the developed solution on partially disabled neurodegenerative disease patients in cooperation with practicing clinicians.
Wireless biomedical sensors should dramatically reduce the costs and risks associated with personal health care while being more and more exploited by telemedicine and efficient e-health systems. However, because of the large power consumption of continuous wireless transmission, the battery life of the sensors is reduced for long-term use. Sub-Nyquist continuous-time discrete-amplitude (CTDA) sampling approaches using level-crossing analogto- digital converters (ADCs) have been developed to reduce the sampling rate and energy consumption of the sensors. However, traditional machine learning techniques and architectures are not compatible with the non-uniform sampled data obtained from levelcrossing ADCs. This project aims to develop analog algorithms, circuits, and systems for the implementation of machine learning techniques in CTDA sampled data in wireless biomedical sensors. This “near-sensor computing” approach, will help reduce the wireless transmission rate and therefore the power consumption of the sensor. The output rate of the CTDA is directly proportional to the activity of the analog signal at the input of the sensor. Therefore, artificial intelligence hardware that processes CTDA data should consume significantly less energy. For demonstration purposes, a prototype biomedical sensor for the detection and classification of sleep apnea will be developed using integrated circuit prototypes and a commercially available analog front-end interface. The sensor will acquire electrocardiogram and bioimpedance signals from the subject and will use data fusion techniques and machine learning techniques to achieve high accuracy.
The goal of this project is to design and evaluate efficient heterogeneous resource management by adaptive power control, throughput enhancement and interference management for D2D communication. The originality is to exploit machine learning (ML) techniques to improve the existing state of the art works. Further, by exploiting unmanned aerial vehicle (UAV) for weak signal detection, and devices accurate position evaluation is an important objective. The deployed setup with UAV assisted connectivity is one of the novel contribution of this project. In addition, context aware and reliable D2D multi-hop routing and network connections to ensure high end-to-end throughout and low end-to-end energy consumption and delay is another core objective.
The goal is to create more efficient impedance spectroscopy methods and microelectronic tools for experimental research in physics, biology, materials science, and technical and medical diagnostics. The objective is expected to achieve by combination of information technology knowledge with achievements in microelectronics. Attention is concentrated on new algorithmic and mathematical methods for the research of spectral analysis methods (simultaneous time-frequency treatment, fractional Fourier transform, orthogonal transformations) for synthesis of short-term and broadband signals with the required excitation spectrum and ensuring the readiness for their electronic generation. Such the binary and ternary pulse sequences are investigated, implementation of which gives an ability to analyze the response signals with a maximum speed and amount of information flow. A demo devices will be developed for demonstrating the achieved scientific results in cognitive impedance spectroscopy.
Tackling the various societal, economic and environmental challenges faced by the EU can be supported by ICTbased solutions such as Wireless Sensor Networks, RFID, Internet of Things. R&D in so-called smart embedded and energy efficient electronics is increasingly important so that such solutions perform adequately, reliably and securely, adapt to changing conditions, and be energetically less visible as their number grows; i.e., future electronics should have cognitive functions deeply embedded into them.Establishing an ERA Chair at T.J. Seebeck Department of Electronics, Tallinn University of Technology (under the activities in the field H2020 WIDESPREAD-2-2014 ERA Chairs), will help it keeping abreast with the above research specialization by increasing its research capacity in cognitive electronics related topics such as new architectures, methods and tools for energy-efficient sensor signal processing, new sensor technologies with improved yield, and efficient communication techniques for autonomous systems and RFID and NFC solutions. Promising applications include pervasive ambient medical/health monitoring, inspection of the structural health of materials and constructs, smart transportation and smart energy distribution. The main task of the ERA Chair will be to breathe new competences, federate resources, and increase the integration of existing research activities by building a coherent research framework in the Thomas Johann Seebeck Department of Electronics.