Technology Transfer Experiments (TTX) financially supported by TETRAMAX

April 2020
E-FLIGHT: Energy consumption optimization at FLIGHT controllers level for blood and hemocomponents delivery through autonomous UAV

The scope of the E-FLIGHT TTX proposal is to implement energy consumption optimization strategies for dramatically improving the performance, and consequently, the industrial and commercial impact of LEONARDO, the smart blood and hemocomponents delivery system through autonomous drones.

FADA, Fundacion Andaluza para el Desarrollo Aeroespacial, Spain
ESGR: Edge Snapshot GNSS Receiver

On request, the TTX brief description will be published at the end of the TTX.

Universitat Autònoma de Barcelona (UAB), Spain
Loctio, Greece
IMLIC: IMproved performance Li-Ion Capacitor system based on low-energy computing for IoT device

On request, the TTX brief description will be published at the end of the TTX.

Aristotle University of Thessaloniki, Greece
Koral Technologies, Italy
LO-CODIFI: LOw COmplexity DIrection FInding

IoT devices can be improved by running multi-layer neural networks. Machine-learning models show impressive accuracy. We plan to improve our wearable with 1) a better direction detection accuracy 2) lower power consumption 3) latest generation BLE chipsets and microcontrollers.

ETH Zürich, Switzerland
Wagoo Italia, Italy
RadMonIC: Radiation monitoring with IC

On request, the TTX brief description will be published at the end of the TTX.

Integrated Detector Electronics AS, Norway
ENVINET, Germany
SWAN: Severe Weather Analysis and Nowcast

The SWAN objective is to provide a proof-of-concept of a novel Decision Support System solution for storm and flood hazard based on short-term predictions in the Mediterranean countries. Artys’ technology is an IoT-driven rainfall monitoring system that will be transferred to Meteorage by means of a licensing agreement. SWAN is an unprecedented solution for the resilience of communities, industria.

Artys, Italy
Meteorage, France
TRU IMC: Transfer of Radar Based Avionics for Uncontrolled Instrument Meteorological conditions (UIMC)

This TTX is about transferring miniaturized low-energy radar hardware and firmware that prevents drones and helicopters to crash into obstacles, birds and each other. Radar allows (auto)pilots to see through bad visibility conditions. The airspace thus will become safer and the transferred technology might open up possibilities for electric flights over shorter distances throughout the EU.

Radar Based Avionics, Netherlands
FLARM Technology, Switzerland
VLP-Automation: Task Automation based on Visible Light Positioning and blockchain

Task automation is an emerging technology for enabling self-configuration and adaptation of services and sensors and it is one of the enabling technologies for IoT. Location based services are one of the most popular services that take advantage of both task automation as well as positioning services. This project aims at providing a Task Automation Platform based on Visible Light Positioning.

Universidad Politecnica de Madrid, Spain
BEIA Consult International, Romania
WiForAgri 2021: Smart Agriculture low-power IoT / Edge-Computing module

On request, the TTX brief description will be published at the end of the TTX.

Primo Principio, Italy
University of Salamanca, Spain
xDeep Neuro IIoT 4.0: eXplainable Deep NeuroFuzzy Learning for fatigue detection and predictive maintenance in Industry 4.0 using low-power IIoT devices

The main objective of this project is to apply new techniques based on eXplainable Deep Fuzzy Learning for the detection of fatigue and predictive maintenance of rotary elements in Industry 4.0 based on their vibrations collected by multiple low-power and low- cost IIoT devices. This approach will allow not only to predict future failures in rotary elements, but also to explain the causes.

AIR Institute, Spain
Technická diagnostika, Slovakia
February 2020
MEATRACK: Miniature gas sensors for real time tracking of ‘meat freshness’ in refrigerators to reduce food wastage and health risks for consumers

MEATRACK aims to increase the smartness of refrigerators by developing and testing minature gas sensors for tracking real time freshness of meat (beef in this project) using a patented gas sensing technology from IM2NP and combined with AI tools of NVISION and IoT software platform of S&C. NANZOZ will develop the required electronics for sensor and fabricating the prototypes.

Sensing & Control Systems S.L., Spain
NANOZ, France
NVISION Systems and Technologies, Spain
Aix-Marseille University, France
RAMSES: Rfid for Advanced Medical SEnSing

This TTX will transfer the University of Salento existing IP on RFID-based CLEC to the SME BAGATIN by defining, supported by the Institute of Clinical Physiology of CNR- Italy, a new RFID sensor/computational tag enabling the unobtrusive monitoring of patients to tailor medical treatments based on real-time data. SME ION Solutions will perform productization/expansion in other market segments.

University of Salento, Italy
ION Solutions, Serbia
Poliklinika Bagatin, Croatia
National Research Council of Italy, Italy
December 2019
CORONA: Distributed Ledger Technology (DLT)-Based Collaborative Robotics for a Low-Energy Machine Economy in Manufacturing Environments

The brief description of this experiment will be published at the end of its implementation phase, as requested by the TTX proposers.

University of Ljubljana, Slovenia
Pumacy Technologies, Germany
LV-EmbeDL: Low-Voltage FPGA-based Embedded Deep Learning for Improving Energy Efficiency

LV-EmbeDL will extend the EMBEDL AB’s Deep Learning (DL) optimizer (EmbeDL) with BSC’s aggressive undervolting technology (supply voltage underscaling below the nominal level) to maximize the energy efficiency of embedded FPGA-based DL systems. LV-EmbeDL will be utilized by the industry partner’s customers in domains like autonomous cars, telecom, and IoT.

EmbdDL, Sweden
Barcelona Supercomputing Center (BSC), Spain
RAINWAVE: An innovative RAINfall monitoring solution based on the combined used of microWAVE links and radar

The RAINWAVE transfer of technology project aims at providing a proof-of-concept of a novel Decision Support system solution for environmental monitoring in France by transferring the Artys’ IPs and knowledge on IoT low-power wide-area network of sensors to NOVIMET by means of a licensing agreement. Artys and NOVIMET will also agree on the exclusivity option in some specific states.

Artys, Italy
SANTO: Self leArNing Tank mOnitoring system

Over 50% of Diesel fuel is supplied via mobile and non-commercial industrial tank systems which in their vast majority do not offer any monitoring infrastructure. Key reasons are the very heterogeneous tank constructions, whose components are provided by numerous suppliers, and a sensor technology as key element that is designed for very specific use cases concerning tank form, size, or material.

Universidad Autónoma de Madrid, Spain
KAPITEL D, Austria
November 2019
ANDREAS:Artificial intelligence traiNing scheDuler foR disaggrEgAted resource clusterS

Today, artificial intelligence (AI) and deep learning (DL) methods are exploited in a wide gamut of products. DL models are trained on GPGPU systems, achieving 5-40x speedup wrt CPU-based servers. ANDREAS develops advanced scheduling solutions optimizing DL training run- time performance and their energy consumption in disaggregated GPGPU clusters. 2x speed-up and 50% energy savings are expected.

Politecnico di Milano, Italy
7bulls, Poland
E4 Computer Engineering, Italy
LEMON System:Low-Energy Mobility Optimisation and Navigation System

LEMON system allows to study existing city infrastructure and patterns of bicycle usage by cyclists to improve city micro-mobility. In addition, it counts with an anti-theft functioning mode. Adaptation of the system to Narrowband-IoT networks will allow to boost the battery autonomy from 40 days to 10-12 months in active tracking mode. The enhanced product will be tested in a pilot in Spain.

Sofia University, Bulgaria
KMB Lab, Italy
Actum4 Innovation, Spain
November 2019
BLEeper: A low-cost outdoor location tracking solution for shoreline safety

BLEeper is a patent-pending approach that utilizes low-cost solar-powered water-proof Bluetooth beacons across geo-fenced shoreline areas (land and on coastal water buoys), in order to deliver high-accuracy location tracking for persons equippedwith any type of low-cost Bluetooth wearable (e.g. wristbands, life-vests). BLEeper delivers superior coastal surveillance, compared to any other available solution, leading to significantly increased levels of safety during shoreline activities.

Telecommunication Systems Research Institute, Greece
H-Beacon: Soil Humidity Prediction; the Beacon Approach

This TTX considers soil humidity prediction system based on the Received Signal Strength Indicator (RSSI) generated from the underground LoRa beacon and related Machine Learning techniques. As a consequence, given energy efficient solution is cost effective and easier to maintain due to the prolonged battery lifetime. Such robust, but simple technology is a great candidate for becoming a strong competitor in the smart agriculture market.

University of Split, Croatia
SolaH: Smart Solar Heating Controller

The goal of the project is to implement a low energy IoT solution for smart home automation. The proposed solution has advantages such as lower price, lower energy consumption, many features, higher reliability, etc. andcould be used for many applications. Our first use case is to develop a smart solar heating controller using ultra low energy processor, cutting-edge techniques and know-how for additional saving.

Sofia University, Bulgaria
March 2019
CLEC PV: CLEC Blockchain Technology for Photovoltaic Power Purchase Agreements

Bettergy, Spain
ReMoni, Denmark
Tecnalia, Spain
PROMIoTOR: Low-Power Internet of Things and Artificial Intelligence for the sustainability of processes in Smart Farming

TAMIC, Spain
EMBIO Diagnostics, Cyprus
AIR Institute, Spain
January 2019
CLEC-Submetering: Manage your Technical Installations by Clamp-on AI Resource Monitoring

EnergySequence is an energy efficiency web intelligence platform delivering data driven energy conservation measures for the industry sector, ReMoni’s smart sensors will power up real time performance by customizing its edge computing capabilities, and extend deployment features through an ad-hoc wireless sensor network for heat, electricity and flow, with energy harvesting capabilities.

Bettergy, Spain
ReMoni, Denmark
CPU-FIN: Toolset for the Integration of Fast and Accurate Microarch. Level Reliability Assessment of CPUs in Resiliency and Functional Safety Analysis Procedure

IROC Technologies, France
University of Athens, Greece
HS-CHAR: High Speed Characterization of Mass Storage Devices

NplusT intends to extend its product line with a new technology, targeting the high-speed characterization of non-volatile memory (NVM) devices. This feature is essential for mass storage (SSD, ...) makers in the optimization of their products. PCBDesign will transfer its high-speed communication technology, in order to follow the NVM roadmap: increased density, higher speed, lower voltages.

save_altTTX results

PCB Design, Hungary
NplusT Semiconductor Application Center, Italy
NIPOLECS: Non-Intrusive Power Monitor for Low-Energy Computing Systems

Effective power measurement is critical for the efficient development of Customized Low-Energy Computing (CLEC) systems. The NIPOLECS project will reduce the selling price of NTNU’s non-intrusive Lynsyn power measurement board by 3X and thereby create a competitive product to be sold by Sundance.

Norwegian University of Science and Technology (NTNU), Norway
Sundance Multiprocessor Technology, United Kingdom
RAAC: Room Acoustics Analysis in the Cloud

The TTX brief description will be published at the end of the TTX.

save_altTTX results

Abinsula, Italy
MK3 storitve d.o.o., Slovenia
November 2018
MIP: Magnetic Information Platform

MIP is a vision of a magnetic data storage technology tailored for industrial applications and consumer products, to be used as a universal rewritable data carrier. This brings an advantage over competing technologies, such as barcodes, etc. Stored information in components can be updated during their life cycle. The information is not visible, and the medium has high temperature and chemical resistances. Hence, the stored data is inherently safe, reliable and suitable in many applications.

Gottfried Wilhelm Leibniz Universität Hannover, Germany
REMAP: Remote rEsource Management hardware IP for disAggregated Platforms

This project presents the REMAP IP, a hardware manager for low-latency chip-to-chip interconnection, targeting low-energy disaggregated platforms and datacenters. REMAP enables on- demand system scaling; processing nodes can dynamically hot- plug remote resources (e.g. memory, accelerators), following application needs on performance and / or dataset sizes. The IP is already tested, has a very light resource / energy footprint, and thus easily fitting into small low-power MPSoCs.

Foundation for Research and Technology – Hellas, Greece
TooFF.IN: Tool Failure ForecastiIN is an IoT integrated platform consisting of a NBIoT multimodal sensoring device for the characterization and position tracking of construction tools. By attaching a universal sensor to the outer casing of any construction tool, we can forecast failures, enforce preventive maintenance and prevent thefts. A SaaS model will be examined that provides progressive tariff billing, therefore incentivizing clients to gradually adopt our service and severely minimize their operational costs.

National Center for Scientific Research “DEMOKRITOS”, Greece
UnifiedAOTool: Unified Analytics & Optimization Tool

Based on IIoT Infrastructure and Big Data Analytics technology our portable software solutions enable for highly sensitive process monitoring and optimization of industrial automated (e. g. manufacturing) processes. The implemented tools are based on generic algorithms for data driven modelling and additional process specific services and use information extracted from existing control and process layer data.

Gottfried Wilhelm Leibniz Universität Hannover, Germany
May 2018
BLEUN: Low consumption Geolocation Urban networks based in BLE (Bluetooth Low Energy) Trackers

This project aims to build urban networks based in intercommunicated nodes made of BLE (Bluetooth Low Energy) trackers to deploy multiple services based in geolocation at low cost and extremely consumption.

Intelligent Parking, Spain
Etelätär Innovation OÜ, Estonia
SEMAB, Spain
Eco-Rural-IoT: Application of techniques and intelligent algorithms aimed to reduce the consumption of power and water in mixed farming environments by means of

The main objective of the Eco-Rural-IoT project is the reduction of the consumption of power, water and even phytosanitary treatments through the research and innovation in techniques and intelligent algorithms which will be incorporated to the unified Nebusens' Rural-IoT platform, aimed at the management of farming resources in the agriculture and livestock sector by means of IoT devices.

save_altTTX results

Instituto Superior de Engenharia do Porto, Portugal
Nebusens, Spain
TAMIC, Spain
Rancho Guareña Hermanos Olea Losa, Spain
Nox.Box: Mobile NOx Sensor component for real time large-scale monitoring and platform

NOx emissions are a societal challenge in Europe due to the adverse health effects it causes. Currently the monitoring of such gas is performed by expensive and stationary sensor modules. Nox.Box will offer a mobile low cost, low-power consuming alternative to monitor NOx on large scales and with high temporal and spatial resolution and an online control platform.

save_altTTX results

Universidad Autónoma de Madrid, Spain
Cleopa GmbH, Germany
Sensing & Control Systems S.L., Spain
February 2018
Carrots: Cooperative ARchitecture for gaRdening with Open moniToring Systems

Tomappo is a digital gardening assistant enabling anyone to grow their own vegetables. Within Carrots, Lifely’s social sensors will be customized for use with Tomappo. This will add new dimension to Tomappo leading to a better product for users and new revenue stream for company receiving technology, while also benefit the owner of the technology by providing a new use-case for their sensors.

save_altTTX results

Lifely, Italy
PROVENTUS, računalniške storitve, d.o.o., Slovenia
DPUsim: Simulation Environment for an In-DRAM Processing Unit (DPU)

The simulation environment enables the full integration of UPMEM’s DPU in a complete DRAM/Controller simulation framework. This is an essential key to maintain a seamless transfer of the RTL based DPU design into DRAM technology.

save_altTTX results

Technische Universität Kaiserslautern, Germany
UPMEM, France
EVErMORE: Energy-efficient Variation awarE MulticORE

EVErMORE TTX experiment aims at developing the next generation GAP-8 IoT processor from GreenWaves Technologies. Exploiting the adaptive management architecture for process and temperature compensation developed at University of Bologna, coupled to the low-voltage capabilities of 22nm FD-SOI technology, is expected to improve the energy efficiency of current generation GreenWaves Technology processors by 6x, enabling new applications and opening new market opportunities.

save_altTTX results

Università di Bologna, Italy
GreenWaves Technologies, France
HeartStep: Heart and Activity Data Fusion

In the scope of the proposed TTX project, an upgraded system prototype will be implemented, with an actual SAVVY®ECG sensor, by connecting the accelerometer sensor to the SAVVY processor through an available serial interface, by integrating the accelerometer firmware into the SAVVY software and by incorporation the posture and activity data into the existing ECG radio packets.

Ruđer Bošković Institute, Croatia
SAVING trgovina in storitve d.o.o, Slovenia
TEBIX: Tetramax Emergency Beacon Integration eXperiment

Integration of the Montr Narrowband IoT equipped emergency button in the Smarthelp ecosystem. With this integration emergency messaging will reach a next level in terms of speeding up the process of alerting emergency services with all the specific information they need.

save_altTTX results

Montr Safety Solutions, Netherlands
Rad AS, Norway
TETRaWIN: TEchnology Transfer of computational-Rfid Wirelessly-powered IoT Nodes

This TTX will transfer the University of Salento recognized skills on wirelessly-powered Computational-RFID technology for IoT to the SME Spica, by defining a new cost-effective battery-less CLEC-based tag enabling the smart traceability of fresh and frozen fish. By performing computation, communication, and sensing to check the food product integrity, the solution will improve the SME business.

University of Salento, Italy
Spica Sustativi d.o.o., Croatia
TETRAMAX consortium partners’ application experiments
Advanced Anti-Debugging Techniques (AADT)

In the ASPIRE FP7 project, Ghent University developed a strong form of anti-debugging protection, based on self-debugging. By including a self-debugger component into an application that needs to be protected against reverse-engineering or tampering, attackers can no longer attach their own debugger. In many cases, this severely complicates attacks. To prevent that attackers detach the self-debugger, part of the original application functionality is migrated into it. Detaching the self-debugger then breaks the application. The developed anti-debugging technology from ASPIRE was already transferred to Nagravision prior to this project, but several potential weaknesses had also been identified, related on the one hand to a lack of stealth in the interfaces between the application and the self-debugger and on the other hand to the fact that they are still coupled loosely, as the self-debugger itself can still be debugged.

Early research results in the Computer Systems Lab at Ghent University hinted that these weaknesses can be overcome, and hence that additional techniques might potentially be of interested to NAGRA. This yielded the raison d'être of this project, namely making the early research results more mature to allow for a better assessment of the potential value for NAGRA.

Ghent University, Belgium
Nagravision, Switzerland
Compiler Fuzzing through Deep Learning (DeepSmith)

Compiler fuzzing is a well established technique for stress testing compilers. Generating random programs for fuzz testing is a challenging problem, typically requiring stochastic enumeration from a hand-coded programming language grammar combined with rigorous static and dynamic analysis to avoid undefined or unreproducible behaviour. Developing such tools is laborious and time consuming.

This project developed a new deep learning-based fuzzing tool for the industrial partner to explore the viability of deep learning neural networks for testing Java compilers and runtimes. The fuzzer will be used to test and identify bugs in IBM's OpenJ9 and OMR projects, making them more safe and robust.

Compared to state-of-the-art grammar based approaches, the fuzzer is simpler, produces small interpretable test cases, and has a lower cost to maintain and extend to new language features.

University of Edinburgh, United Kingdom
IBM Nederland, Netherlands
Improvements to LLVM's vectorisation and function-merging optimisations (LLVM SLP & FMSA)

This project concerns the transfer of two compiler optimisations developed and presented by the first author in two different peer-reviewed papers. The first optimisation is the Look-ahead SLP that improves upon the existing SLP vectorizer in LLVM. This optimisation was published in the International Symposium on Code Generation and Optimisation (CGO), 2018. The second optimisation is the Function Merging by Sequence Alignment, a novel optimisation for reducing code size. This optimisation was published and awarded best paper in CGO 2019.

University of Edinburgh, United Kingdom
Codasip, Czechia
Libro & Libra: wireless scale and mobile app for personalized nutrition tracking (BALLERINA)

Today there are more and more people with special nutritional needs (e.g. people with food allergies and intolerances; athletes; pregnant and lactating women; patients with diabetes, hypertension, chronic kidney disease, phenylketonuria, etc.), who need to avoid or limit specific foods or nutrients in the diet. For this reason, information about foods and nutrients needs to be provided in a user-friendly way to become useful. Recently, advanced mobile apps based on artificial intelligence have been developed to provide this kind of information on the basis of food images taken by smartphones (e.g. Calorie mama, Bitesnap, etc.). However, they still struggle with the problem of the estimation of food quantities (volumes). Therefore, in the frame of Ballerina, the partners have developed a new product - based on the JSI’s pocket-sized BLE kitchen scale technology “Libra” - that enables accurate measurement of the food mass in real-time. To prove its efficiency, we connected it with Libro - a mobile app for advanced dietary analysis.

Institut Jozef Stefan, Slovenia
Nutritics, Ireland
Off line mobile route and recommendation for Touristic Companies (Off-Tour)

Off-Tour is a fully functional energy-optimised library for Tourist Apps recommendation and routing based on Sparksee Mobile Graph Database1 which has been ceded to DAMA-UPC by Sparsity. The library could now potentially be used by any tourism app to leverage their functionalities by having out-of-the-box recommendation based on tags of the POIs and the tourist’s tastes obtained from questionnaires or Social Media.

ENCO Consulting, Italy
Silicon Microcantilevers and Microfluidic Fitting for Air Quality Monitoring (SiMMF4AQM)

General concept for Air Quality Monitoring (AQM) is based on simultaneous measurement of multiple physical values and concentrations of different components of the air at one-and-same point. Also, it is preferable one-and-the same principle of measurement to be exploited for assessment of each of the abovementioned values and concentrations. Piezoresistive Silicon microcantilevers, also called “self-sensing cantilevers”, are promising candidates to enable the said concept.

Partners in project the SIMMF4AQM are two SMEs from Bulgaria and France: first partner, AMG Technology (AMGT) is active in development of novel MEMS devices with integrated piezoresistive feedback and electrothermal (ET) actuation; second partner, EFFICIENCE Marketing (EfM) develops and promotes to market novel AQM systems. Areas of expertise of both parties have been successfully merged during the internal TTX by demonstrating functionally integrated cantilever sensors, incl. microfluidic member. Sensors are capable simultaneously to measure multiple values at power consumption for actuation below 1μW/cantilever.

Results are paving the road towards long-term partnership for penetrating the global AQM market.

AMG Technology, Bulgaria
Efficience Marketing, France
Techmo English ASR TTX (TEA)

The task was to adapt Techmo Automatic Speech Recognition (ASR) to international market by making English version. Data were collected, processed and used for retraining of models which previously were used for Polish. ASR is a technology that has been evolving for several decades. Techmo ASR is a system developed by the Techmo for automatic recognition of Polish speech. It is used as a voice interface for applications or call steering. It can be used as an acoustic search engine or for creating voice notes, as well as for reporting energy failures. It is based on the latest achievements in technology (deep learning) to achieve low resources and low energy computing.

TTX aimed in developing new version for English markets which will be distributed together with a partner. English speaking countries are by far the largest market for ASR solutions. It is also a necessary step for a Techmo to have English version to speed up export and negotiations with investors.

Techmo, Poland
Syslore, Finland


TETRAMAX is a Horizon 2020 innovation action within the European Smart Anything Everywhere (SAE) initiative in the domain of customized and low-energy computing for Cyber Physical Systems and the Internet of Things. As a Digital Innovation Hub, TETRAMAX aims to bring added value to European industry, helping to gain competitive advantage through faster digitization. The project partially builds on experiences with the TETRACOM project during 2013-2016. TETRAMAX was launched in Sep 2017 and runs until Aug 2021.