CY.R.I.C CYPRUS RESEARCH AND INNOVATION CENTER LTD

Gait dynamics’ monitoring and Energy Expenditure (EE) calculation is of high importance for patients with chronic diseases affecting normal walking, for individuals after injuries & surgery, as well as for older adults, in order to early detect and correct gait problems or accelerate rehabilitation. The need extends to the multibillion industry of professional athletes for a) load management (injury prevention, performance optimisation), b) accelerated recovery from a lower limb injury, c) running efficiency optimization and precise body control. Due to the significant drawbacks of market available systems (high price, difficult to use software, necessity to operate under expert supervision, intrusiveness), gait analysis is used less often than would actually be required. For patients & clinics, this has an impact on rehabilitation time & cost, as well as on the timely detection of certain medical conditions. For athletes, this has an impact on costs related to delayed rehabilitation, but also on increased cost for injuries that could have been avoided. insofeet is a completely non-intrusive insole for measuring accurately key gait dynamics’ parameters and EE. The insofeet insoles are capable of fitting in different shoe types. The insofeet insole integrates highly accurate miniature force sensors in a customisable design, adaptable to the application. Sensor measurements are collected in real-time, processed through validated algorithms and presented through a friendly interface. What differentiates insofeet from the competition is its unparalleled accuracy, comparable to hi-end professional solutions at a price 15 times lower. An EU/WO patent application was submitted by CyRIC. Our goal is to bring the insofeet solution to market, after preparing an elaborate business plan. According to our initial plan, within 5 years from insofeet commercialisation, revenues will reach an annual total of approximately 7.8 M and 25 new jobs for CyRIC will be created.

Today’s fiber optical sensor systems show very promising performance and are well suited for numerous sensing tasks. Despite the enormous progress that has been made for fiber sensors, these systems are still more of a niche solution. Adaptive, modular sensor systems with flexibility regarding the sensing concept, fiber-based sensor type, sensor or sensor network configuration and measured quantities are highly desired but not available at this time. For example, already installed fiber infrastructure along railroad tracks or in buildings are hardly used in such systems. Nevertheless, there is an enormous potential to realize sensing networks by using the existing fiber infrastructure for both purposes, carrying data and perform sensing. Furthermore, a cloud-based digital control software defined setup, advanced signal processing with methods of machine learning, digital twin technologies and cloud-based interfacing to monitor the system performance are required and motivate further research and development in this field. There are though specific challenges to be addressed: SoFiN addresses these challenges, contributing to adaptive photonic multi-sensing systems with focus on: a)developing & testing a novel flexible, adaptive, modular, software-defined sensor platform b)studying ways to establish sensing options in existing communication fiber networks c)developing new laser types, sensor elements & sensing approaches compatible with fiber sensing d)studying concepts for ML-based signal processing and digital twin sensor system modelling e)developing machine learning tools that can handle large amounts of incoming data f)researching on ML tools that can enhance the signal-to-noise-ratio (SNR) and provide ultimate sensitivity g)developing centralized processing unit that integrates all sensory input data h)developing and implementing concepts for cloud-based system control i)performing a system test in a near to operational environment in different case studies

ENCASE will leverage the latest advances in usable security and privacy to design and implement a browser-based architecture for the protection of minors from malicious actors in online social networks. The ENCASE user-centric architecture will consist of three distinct services, which can be combined to form an effective protective net against cyberbullying and sexually abusive acts: a) a browser add-on with its corresponding scalable back-end software stack that collects the users’ online actions to unveil incidents of aggressive or distressed behavior; b) a browser add-on with its associated scalable software stack that analyses social web data to detect fraudulent and fake activity and alert the user; and c) a browser add-on that detects when a user is about to share sensitive content (e.g., photos or address information) with an inappropriate audience and warns the user or his parents of the imminent privacy threat. The third add-on has usable controls that enable users to protect their content by suggesting suitable access lists, by watermarking, and by securing the content via cryptography or steganography. The three browser add-ons and the back-end social web data analytics software stack will be assessed with user studies and piloting activities and will be released to the public. The foundation of the research and innovation activities will be a diligently planned inter-sectorial and interdisciplinary secondment program for Experienced and Early Stage Researchers that fosters knowledge exchange. The academic partners will contribute know-how on user experience assessment, large scale data processing, machine learning and data-mining algorithm design, and content confidentiality techniques. The industrial partners will primarily offer expertise in production-grade software development, access to real-world online social network data, and access to numerous end-users through widely deployed products.

Transport related emissions and urbanisation are creating an unparalleled demand for less polluting and efficient means of moving. Tackling the challenge is imperative and it calls for comprehensive understanding of the landscape, its every aspect and innovative mindset. It is a well-known fact that electric vehicles are a big part of the solution (combined with renewable energy production). We aim at developing and demonstrating an innovative, modular vehicle concept that is just perfect for the urban needs: zero emission, compact, safe and rightsized for the mission. Furthermore, we aim at intensifying the utilisation of the vehicles through versatile designing to promote, e.g., multipurpose usage and shared concepts. The key technical innovations of our RECONFIGURABLE LIGHT ELECTRIC VEHICLE, REFLECTIVE, vehicle are: 1) modular, scalable, electric powertrain and reconfigurable interiors fit from L7 quadricycles to M1/A vehicles; 2) supreme structural and active safety proven in Euro NCAP crash test and real life experiments of our L7 demonstrator vehicles; 3) added usability and comfortability through adaptable charging solution combining conductive and wireless charging and limited automated features. To conclude, we aim at introducing a L7 demonstration vehicle that meets the highest quality and safety standards with an affordable price making it an irresistible choice for any urban environment and use case. No such solution exists at the market and our primary aim is to bridge this gap.

Pervasive and on-line water quality monitoring data is critical for detecting environmental pollution. However, it’s not easy to gather such data, at least not for all contaminants. Currently, water utilities rely heavily on frequent sampling and laboratory analysis in order to acquire this information. For this situation to be improved, portable and high-performance devices for pervasive water quality monitoring are required. Towards this end, there has been growing interest in expanding spectroscopic methods beyond the 2μm range of the infrared spectrum. That region of the spectrum is home to many vibrational & rotational absorptions of compounds related to water quality. Unfortunately, water itself is a strong absorber of infrared light. Thus, such methods were restricted to laboratory settings until now. WaterSpy addresses this challenge by developing water quality detection photonics technology suitable for inline, field measurements, operating in the 6-10 μm region. The solution is based on the combined use of advanced, tuneable Quantum Cascade Lasers and fibre-coupled, fast & sensitive Higher Operation Temperature photodetectors. Together with these new components, optimized laser driving and detector electronics as well as laser modulation concepts will be developed. Attenuated total reflectance spectroscopy will be used to give rise to the biochemical profile of the surface chemistry of the sample. Targeted analytes will be specific heterotrophic bacterial cells. Several novel techniques are employed in order to increase the SNR, including antibodies capable of binding the targeted analytes and a novel pre-concentration method. WaterSpy technology will be integrated, for validation purposes, to a commercially successful water quality monitoring platform, in the form of a portable device add-on. WaterSpy will be used in the field for the analysis of critical points of water distribution networks. This will be demonstrated in two different demo sites in Italy