IDRD

Company info:

Name: Ubotica Technologies Ltd.
Date founded: 2016
Number of employees: 12
Location: Dublin, Ireland; Ciudad Real, Spain

Irish SME focused on delivering computer vision and AI based solutions on-the-edge.

www.ubotica.com

Partners:

IDRD: In-Line Diabetic Retinopathy Detection

Challenge

Diabetic Retinopathy (DR) is the leading cause of vision loss in adults aged between 25 and 60, with a recent study estimating that the number of people worldwide with DR will grow to 191 million by 2030. Elsewhere, it has been estimated that the cost of DR to the UK economy will reach £97,000,000 by 2036. When DR is caught early, treatment is effective at reducing or preventing vision loss and while a very small number of countries have national screening programmes for DR detection in place, they are not commonplace and are costly to run.

Solution

In-line Diabetic Retinopathy (IDRD) is a light weight Computer Vision and Artificial Intelligence solution for detecting the presence of DR indicators in retinal images on-the-edge, in the specialist fundus cameras that take these images. The solution has been developed around the Intel Movidius Myriad2 Vision Processing Unit (VPU), which pre-processes the retinal images using its on-board image filtering capabilities and then applies an Artificial Intelligence Convolutional Neural Network (CNN) to assess the retinal image for DR indicators. The solution has been designed to assist ophthalmologists to accurately and consistently evaluate and diagnose DR. Ubotica are working with fundus camera manufacturers to introduce IDRD to the marketplace by 2021.

FED4SAE Support

A significant challenge in the deployment of AI based solutions is in the supervising of decisions of the CNNs which are at the core of these systems. Through the FED4SAE program we are working with fortiss to integrate their Neural Network Dependability Kit (NNDK) into IDRD. Among other features, it supports neural network (NN) verification to ensure the results do not lead to undesired behaviours, test-case generation and quality metrics computation to increase model robustness, and runtime monitoring to check if a decision of a deployed model is supported by the training data. In this way we are introducing a level of confidence to IDRD that heretofore was not possible, giving us a credible Verifiable AI element to our offering. In addition, working with our FED4SAE partners fortiss, Intel and Blumorpho has had a very positive impact on both our technical and business capabilities.

Impact

Deploying our IDRD solution in fundus cameras will significantly enhance the role of both the cameras and the ophthalmologists who use the cameras in the eye care paradigm, with further advances anticipated with the introduction of detectors for other pathologies, such as Glaucoma and Hypertension, all based on the same underlying hardware. With the integration of the NNDK the product offering has been significantly enhanced, with its supervisory role on the decisions being made by the CNNs delivering a significant benefit to the integrators of IDRD.

RobRad

 

Company info:

Name: ASINCO GmbH
Date founded: 2012
Number of employees: 25
Location: Duisburg, Germany

www.asinco.de
www.radarmesstechnik.de

Partners:

Robustification of radar sensors for application in harsh industrial environments

Challenge

Due to the adverse environmental conditions in metal production, essential measurement technologies, e.g. optical and laser-based, reach their physical limits in various fields of application. Thus, observation of relevant process parameters stays fragmented over the whole process-chain.

Radar-based measurement is insensitive to the adverse conditions (e.g. high temperature, dust, air humidity, mist from rolling emulsion or oil) and recording necessary measurement variables with sufficient precision. Due to advancement in innovative signal processing algorithms this is achieved without any discernible disadvantages compared to existing measurement technologies.

Solution

For improving the technological readiness level, well-structured and competently performed experiments and functionality tests are of core importance. Within the metal industry environmental conditions as high temperatures, dust, varying humidity and corrosive gases typically occur within the areas where sensors are located. This hinders many common sensors (optical, laser-based) from reaching their specified functionality.

The objectives within the application experiments in this project can be summarized as follows:

  • Testing and improving sensor performance in terms of real-time capabilities for digital signal processing (sampling time: up to 1 kHz)
  • Testing and improving sensor protection (housing) against harsh environment conditions with long-term continuous load tests against corrosive gases
  • Testing and improving sensor protection (electronic) against harsh environment conditions with long-term continuous load tests with temperatures up to 100°C and variable humidity

FED4SAE Support

The increasing use of sensor intelligence and data preprocessing capabilities will be tackled as well with the use of the industrialized STM. By transferring main raw data processing onto a decentral embedded system included in the sensor, core requirements are provided for effectively implementing the sensing units as self-aware CPS in industrial environments. The simulation of real process environments by exploiting the functionalities of the advanced platforms of the corrosive gases testbed perfectly rounds of the improvement of the technological readiness level of the radar sensors. ASINCO is already closely interconnected within the pan-European community of radar sensors and additionally within the steel producing community. These cross-border collaborations can be further enhanced.

Impact

In close compliance with the targeted objectives of the call, this project tackles the development of further enhancing an already novel and smart solution of a technologically specialized SME. Thereby, it becomes possible to expand ASINCO’s leading position in the target market of providing robust measurement solutions for the metal producing industry.

The initiation and further pursuit of the robustification and market readiness development of radar-based sensors is the main interest for ASINCO. Numerous preliminary talks and discussions with various stakeholders from universities over research institutes to clients, clearly shows that the systems currently available on the market obviously do not meet industrial requirements. There is currently great interest in testing radar measurement technology for applications such as product tracking, geometry and speed measurement and control on hot wide strip mills. The radar-based system technology to be further developed and especially robustified for the industrial application also has the potential to be used in almost every process stage of metal processing, from continuous casting (slabs) and hot rolling (hot strip, heavy plate) to cold rolling and finishing, as well as in long product plants. In a comparison of today’s optically- or laser-based measuring systems, a previously unattained field of application, namely much closer to the process, can be opened up. With the entry of this new measuring technology, possibilities for process improvement with associated energy savings are attained at many points in the metal production process. There is also potential in the use of other materials such as plastics, glass, wood and paper.

INCOMING

 

Company info:

Name: Zannini S.p.A.
Date founded: 1963
Number of employees: 150
Location: Castelfidardo (AN), Italy

Zannini is specialized in the production of high precision machined components for automotive applications

www.zannini.com

Partners:

INCOMING: smart Interface for COnnected MachinING operation

Challenge

In Industry 4.0, the manufacturing world is embracing information and communication technology (ICT) more and more. Applications range from production management to smart material handling, from autonomous vehicles to sensor networks for machine monitoring. To gain the maximum benefit from adopting these systems, production machines must be directly interconnected with the factory ICT.

Making a network connection is only the start: making all machines, sensors and systems interact and play together like a well-tuned orchestra is the actual challenge. Efficient ways must be found to specify these interactions, since conventional programming would be too time consuming. Another significant aspect of this challenge is the need to bridge the technology gap and integrate legacy machines with no or only rudimentary digital networking capabilities.

Solution

INCOMING will develop a new integrated and interoperable solution to connect different types of machines through an open system that can be easily scaled and modified. This will be composed by an open source infrastructure for distributed industrial process measurement and control systems based on the 4DIAC platform, with a STM32 based solution as production machine add-on hardware.

To demonstrate the system functionality, this solution will be installed in three turning machines, with three different generations of machine control technologies. Machine operators and production managers will be able to monitor and control status and parameter data from these machines, enabling them to increase the overall equipment efficiency (OEE) by discovering problems and process inefficiencies faster.

FED4SAE Support

INCOMING will be carried out thanks to support by fortiss for the 4DIAC implementation and to support by ST Microelectronics for the chosen prototype STM32MP1 boards with X-NUCLEO expansion. Business innovation coaching is supported by Blumorpho.

Impact

INCOMING will generate impact in several ways. The first one is to establish a digital infrastructure that allows Zannini to gather operational status data from tool machines, which in turn can be used to improve production management processes, with the goal of increasing the Overall Equipment Efficiency (OEE) of these machines by an amount between 5% and 10%. The second reason is to permit Zannini to gain knowledge about the advantages of open software and hardware platforms for machine connectivity over commercial ones, so as to gain a competitive advantage in a fast changing market. Furthermore, the know-how that will be generated during INCOMING will also introduce the possibility for Zannini to create new services or even products for other companies.

Sentinal

 

Company info:

Name: Sentinum UG
Date founded: 2018
Number of employees: 3
Location: Nuremberg, Germany

Sentinum specializes in the implementation of large-scale wireless sensor networks for municipal use. Starting with the hardware, over the wireless communication up to data storage, evaluation and visualization.

www.sentinum.de

Partners:

An energy-self-sufficient drainage monitoring system for critical event detection

Challenge

Rapid flooding of drainage systems is a well-known but hard to predict consequence of heavy rain that occurs in many climates around the world. The resulting high flow rate and pressure in the duct system can lead to considerable damage to the substance or even worse to detached manhole covers which pose a danger to pedestrians and traffic participants.

Solution

Only with a holistic sensor system an accurate picture of the events in the canal is generated and damage to infrastructure and people can be prevented. By recording the water level, flow rate and pressure, conclusions can be drawn in real time about events in the drainage system. We also record the position of the manhole cover and the presence of harmful gases such as H2S to protect people in the vicinity. The sensor is completely energy self-sufficient and wireless. The communication uses the latest LPWAN technologies. All data is stored by our cloud services and visualized for the customer.

FED4SAE Support

In the implementation of our product, we benefit especially from the partners provided to us via FED4SAE. Our energy self-sufficient sensors require low-power microcontrollers which nevertheless possess a certain performance. For this we use the STM32L4. With its extremely low power consumption in sleep modes it is predestined for our application. Via FED4SAE we have direct contact to ST-Microelectronics and can access this resource and expertise first hand. With the Fraunhofer IISB as test bed, we can simulate the harsh environmental conditions prevailing in a sewer system and analyze its effects in a unique way. Being able to fall back on such practical tests during product development accelerates time-to-market extremely and increases the quality of our final product.

Impact

Our system will affect two different areas. On the one hand, there are hardly any possibilities for planning offices and municipal civil engineering departments to evaluate how their sewer system works. With our system, data is continuously recorded over many years and processed to provide information about changes and anomalies. This opens up a completely new perspective on the planning phase, implementation and, above all, maintenance of the sewer systems.

The second point is increased safety for pedestrians and traffic participants. Injuries and even fatal accidents due to missing manhole covers occur more frequently than they should. Accidents or even drowning due to the tremendous suction of the backflowing water during heavy rain events. With our sensor system, depositioned manhole covers are instantly detected and warnings are transmitted to the relevant authorities. By voice call, sms or email. With this information, communities can act quickly and avoid resulting threats to people and the environment.

Smart-Tunnel

 

Company info:

Name: ISSD
Date founded: 2009
Number of employees: 51
Location: Ankara, Turkey

ISSD is working on system design and integration, digital signal processing, software development and electronic design. The company provides solutions for Intelligent Transportation Systems, Traffic Management and Enforcement Systems.

www.issd.com.tr

Partners:



Smart-Tunnel: Improving automatic incident detection in tunnels

Challenge

There are thousands of vehicular tunnels in use worldwide and that number is expected to continue to grow to alleviate the impact of congested traffic. These tunnels mainly deploy CCTV cameras which are wired back to a central control room where human operators monitor the flow of vehicles to ensure the safety of the tunnel and its users. A known problem is that human operators struggle to scrutinize large numbers of monitors over extended periods of time due to cognitive overload.​

ISSD has developed an Automatic Incident Detection (AID) system and deployed this to multiple sites around Turkey to aid the human operators in their monitoring tasks. These systems analyse parallel video streams from multiple cameras in real-time and provide automated alerts to the operators in the event that an issue is detected which they may need to act upon. This makes their job easier, more accurate and efficient, and makes the tunnel safer for its users.​

The current systems utilize traditional Computer Vision image processing algorithms which suffer from known limitations of this approach. Thus, the challenge is to improve the system accuracy, reliability and performance while extending its capabilities and ideally reducing the hardware costs.

Solution

Neural networks have shown excellent performance in computer vision related tasks. Thus, the new AID system design will utilise neural networks to achieve the desired goals. By augmenting the current AID solution, it is anticipated that the final system will be able to outperform the current system, detecting and tracking the movement of the various vehicle types or pedestrians with higher accuracy and better performance. To achieve this it is planned to use Vision Processing Units (VPU) that are dedicated to video image processing instead of the current reliance on CPUs. This will provide better performance, reduce the system hardware costs and contribute to a scalable architecture.​

FED4SAE Support

Through the EU funded FED4SAE Program, ISSD will be able to apply its many years of experience in tunnel monitoring systems, partnering with fortiss, BLUMORPHO and Intel to deliver this new product.​

Partners will provide ISSD with business innovation coaching and contribute their expertise in product development. Fortiss will contribute technically via their Neural Network Dependability toolkit to reduce the uncertainties inherent in the operation of artificial neural networks. The desired solution is targeting the Movidius Myriad X VPU hardware – the most advanced VPU from Intel which features a Neural Compute Engine with a dedicated hardware accelerator for deep neural network inference. ​​

Impact

The prototype system will be deployed and validated at one of ISSD’s existing road tunnel customers in Turkey. The solution will enable ISSD to have a stronger product offering to improve tunnel safety solutions deployed by authorities. The solution can be deployed to both new and – as a retrofit – to existing tunnel control centre infrastructure and thus bring the benefits of AI enhanced computer vision to these markets.

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OTA Rainwater Management Technology

 

Company info:

Name: OTA Analytics
Date founded: 2015
Number of employees: 7
Location: Devon, UK

OTA Analytics provide real-time logging and analytics services to enable urban drainage systems to be monitored, maintained, valued and controlled.

www.overtheairanalytics.com

Partners:

Artificially Intelligent Rainwater Management Technology

Challenge

In our busy urban settings frequently, there is either too much or too little water. With changes in our climate, growing urban populations and increased hard surfaces in our cities we have seen a significant increase in the risk of flooding and sewer spills. Furthermore, ever increasing pressure on water resources and challenges of potable water availability require rapid implementation of water efficiency measures in cities on every continent. Innovative cyber physical technologies are required in order to resolve two of the World’s most costly challenges of our time.

Solution

Rainwater management systems are dual-purpose solutions; providing water efficiency benefits as well as stormwater management services with associated monetary, energy and carbon cost savings for both consumers and utilities. OTA utilise state of the art IoT technologies, which incorporate Predictive Analytics & Artificial Intelligence with the latest water management and engineering practices.

Our vision is to deliver systems that are low-cost, reliable and scalable across global markets. Such systems bring multiple benefits and target a nexus of the challenges facing the water management sector. They provide an ability to capture, store, reuse and release rainwater incident on individual properties and by doing so improve the potable water supply-demand balance and reduce the likelihood of stormwater related flooding and pollution.

FED4SAE Support

In this experiment we will develop a robust, scalable hardware/software system in the STM32 platform, integrate it with OTA’s middleware, deploy it for testing and validation in the SmartCity Santander testbed and use the subsequent data to develop and refine innovative artificial intelligence based control algorithms, in a realworld setting.

Building on our work since 2015, and with the business development support from Blumorpho and digital catapult, this experiment will accelerate our solution to market in the EU in the near future, where we can enter as a first mover and realise a significant market share.

Impact

When implemented at scale, our system can help mitigate flooding and sewer spills at some of the most challenging catchments and areas, resulting in significant saving (economic, energy and carbon) alongside climate change adaptation and mitigation. Meanwhile, each system can help reduce demand on dwindling potable water supplies. The market size for both flood mitigation as well as water use efficiency is significant, and the solution can be adapted for application across arid, and wet climates.

With the help of FED4SAE platform and collaboration, OTA aims to improve its product and service offering for large scale market demand and become the go-to company for controlling smart rainwater management systems.

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Time4PS

 

Company info:

Name: Fent Innovative Software Solutions S.L.
Date founded: 2010
Number of employees: 8
Location: Despacho 03 – UPV, Pedro Duque, 7, 46022 Valencia

www.fentiss.com

Partners:

Time4PS: Fully integrated development tools for partitioned systems

Challenge

The main goal of the project is to provide a complete set of tools that covers all the phases of the life cycle of the product: from the system design to the final configuration file of the partitioned system.
Goals

  • Connect our customers modelling tool with Time4Sys.
  • Give Time4Sys the ability to define partitioned systems.
  • Connect Time4Sys and Xamber so the timing performance verification is automatically done in Xamber.
  • Demonstrate de capabilities of the partitioned framework developed by means of an application experiment in the space domain.

Solution

The architecture proposal can be seen in figure below, where three tools are connected to define the complete system. A modelling design tool (EEI/XPM) that is used to model the system and generate the deployment and automatic code of the applications, Time4sys to define temporal information and a configuration tool to obtain the static configuration file for XtratuM (Xamber).

FED4SAE Support

Time4PS will contribute to scientific progress of software engineering for mixed criticality embedded real-time systems and it will highlight the increase in quality and effort savings obtained by using an integrated software development lifecycle supported by the appropriate tools. The close interaction of fentISS with FED4SAE partners, notably the Thales Group research team, will enhance the project impact in the scientific community.

Impact

The participation in Time4PS will enable fentISS customers to use more sophisticated tools for modelling, analysis and integration of their system and it will give fentISS the ability to develop further support of their products. Also, it will empower fentISS to gain global competitiveness in three ways. Firstly, it will allow fentISS to enter in customers who are already using Time4Sys. Secondly, it will improve the company products position in large and complex projects. Finally, the project will offer new opportunities to fentISS to enter in adjacent markets such as aviation, railways or automotive.

Safecility

 

Company info:

Name: The Convex Lens
Date founded: 2018
Number of employees: 4
Location: Dublin, Ireland

Safecility’s innovative sensor technology enables property owners to easily meet their statutory obligations to test emergency lighting through automation.

www.safecility.com

Partners:

Safecility: automated sensor solutions for statutory building compliance testing

Challenge

Every year European businesses and public bodies spend €1bn on inspection of Life Safety Systems in public buildings. Emergency lighting testing is a segment of legally required fire safety testing that at present is conducted manually by technicians who inspect, test and affirm the lighting at a minimum four times per year. This is expensive and time consuming with huge potential for human error and thus non compliance. Smart sensor solutions which automate this testing can free up resources while streaming vital compliance data. This allows building owners to make informed compliance decisions resulting in smarter and safer buildings.

Solution

Safecility digitises the antiquated emergency lighting testing process seen within industry. In Europe emergency lighting testing is carried out in person with results recorded using paper in 90% of cases. Safecility replaces human input with wireless sensors which automate scheduled testing and stream the data to asset managers via a software platform. Building owners can be assured of their compliance status in real time through a simple visual dashboard and audit trail.

FED4SAE Support

Safecility will be implemented using the ST Microcontroller BL072Z and validated on the Digital Catapult LoRa testbed infrastructure in London, UK.

Impact

Safecility will automate and digitally record legally required emergency lighting testing while minimising the cost and time involved in maintaining compliance. Developing and validating this type of sensor technology using LoRa has the future potential to offer a wide range of applications which would tackle additional statutory building compliance testing in smart cities.

Safecility is taking strides towards a more transparent and accountable system for fire safety testing in the wake of the Grenfell Tower tragedy. Human error or failures will be drastically reduced resulting in safer buildings and safer residents.

RATE

Company info:

Name: Link Software
Date founded: 2002
Number of employees: 15
Location: Elgazala Technopark, Ariana, Tunisia

http://www.linkconet.com

Partners:

Runtime Architect – RATE

Challenge

Today, one of the major challenges in the Performance Engineering of real-time systems is the integration of design models and runtime aspects. The timing behavior at runtime has to be matched with the design in order to identify the timing failures in design and deviations from the real-time requirements.

Many tools exist for tracing the execution/communication and performing measurements of runtime properties. However, these tools do not allow the integration with system design models – the most suitable level for engineers for performance verification and optimization as well as decision-making.

Solution

RATE will allow the architect performing a continuous system performance engineering cycle between design and runtime, thus ensuring the quality of the running real-time system while reducing the design and development efforts and costs, and getting valuable feedback that can be used to boost the productivity and provide lessons-learnt for future generations of the product.
The following objectives will be fulfilled:

  1. Verify if timing requirements are met in the system execution (CPU) or communication (network/bus) and identify potential timing bottlenecks.
  2. Help the architect understanding the system timing behaviour based on numerical and graphical statistics for the system execution/communication.
  3. Perform consistency check between runtime and models to validate timing related assumptions taken at the design phase.
  4. Help the architect correcting timing errors and exploring design alternatives at the design phase based on the system runtime behaviour before investing time and efforts in implementing and testing.

FED4SAE Support

RATE will integrate the FED4SAE technology Time4Sys. By relying on the Time4Sys design model and the Time4Sys trace model, RATE will automatically benefit from current and future connections to Time4Sys of the various existing model-driven performance engineering tools such as design tools, scheduling analysis and simulation tools as well as tracing tools all at once. This will guarantee high flexibility and add a valuable agnostic character to RATE since it will be possible to easily integrate it in any runtime, design and any scheduling verification environment.

Impact

Runtime Architect gives to the architect access to knowledge on the system timing behavior based on the processing of runtime traces, thus allowing him to easily perform correction during validation and before delivery. Runtime Architect will allow reducing the design efforts (~15% gain estimated) while improving development efficiency as well as validation speed (~30% faster timing validation).

Through the integration of the Time4Sys technology, it will be easy to use Runtime Architect in any runtime, design and timing verification environment, thus offering to our customer a seamlessly integrated solution that will deliver a full, round-trip support for runtime traces analysis, design modelling and timing verification. Performance engineers will be able to rapidly integrate runtime aspects collected from traces into their design models. They will be able to start from runtime traces and then change the system configuration virtually to easily predict the performance impact of modified timing properties of tasks, schedulers or hardware. Runtime Architect will enable performance engineers to quickly iterate their designs as many times as they want, for both new developments and evolutionary extension and optimization of existing systems.

NanoLeak

Company info:

Name: NanoTech Analysis S.r.l
Date founded: 2013
Number of employees: 4
Location: Turin

Operating in the field of fluid and chemical analysis measurements. Company’s vision is to laid the ground for instruments operating at molecular (nano)‐scale.

Nanotechanalysis.com

Partners:

Development of a smart sampling device based on NANOhole LEAKs for analytical instrumentation

Challenge

Miniaturize and digitalize the gas sampling using combination of Nano Electro Mechanichal System (NEMS) and computing power. This will lead to high resolution gas analyzer, multigas detectors, innovative GC-MS portable with electronic control and management signal that can be fully integrated on a chip structure.

Solution

The control of the gaseous flow is made with an array of submicrometric holes that can be open and closed individually (the NEMS device). A process control system can manage each hole individually and can also control the gas flow with a fine granularity (from full array opening to one-hole opening) down to molecular level. The gas sensor signal (mass spectrometer for example) will be used with embedded algorithms to adjust the gas flow to obtain a better sensitivity or signal over noise ratio. The algorithms are implemented on the computer platform from ST (STM32).

FED4SAE Support

The NEMS device will be fabricated using the advanced manufacturing/packaging technology platform of CSEM. An array of submicronic hole will be etched in a membrane and flexible beams will be created to be able to close each hole individually.

Managing the gas flow is done by controlling currents applied on the beam array. This will be achieved using the STM32 platform. Consequently, it becomes possible to realize and implement a complete smart management of the inlet gas flows’ control as a function of the sensor signal.

Blumorpho will help NanoTech Analysis in building business.

Impact

This AE will be core of future gas analyzer that will allow NanoTech Analysis to miniaturize up to a portable system. The application will allow the industry to minimize the risk of introducing NEMS in the device and to have up to date integrated calculation capacity on board (STM32).

The AE experiment will help NanoTech Analysis to validate the use of nanotechnology for gas sampling systems and therefore valorize their patent portfolio.

The help of competent partners (ST, CSEM) will shorten the development time.

The interaction with all the FED4SAE partners will help to refine the marketing strategy of NanoTech Analysis.

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