A novel type of application for the exploration of enclosed or otherwise difficult to access environments requires large quantities of miniaturized sensor nodes to perform measurements while they traverse the environment in a “go with the flow” approach. Examples of these are the exploration of underground cavities and the inspection of industrial pipelines or mixing tanks, all of which have in common that the environments are difficult to access and do not allow position determination using e.g. GPS or similar techniques. The sensor nodes need to be scaled down towards the millimetre range in order to physically fit through the narrowest of parts in the environments and should measure distances between each other in order to enable the reconstruction of their positions relative to each other in offline analysis. Reaching those levels of miniaturization and enabling reconstruction functionality requires: 1) novel reconstruction algorithms that can deal with the specific measurement limitations and imperfections of millimetre-sized nodes, and 2) improved understanding of the relation between the highly constraint hardware design space of the sensor nodes and the reconstruction algorithms. To this end, this work provides a novel and highly robust sensor swarm reconstruction algorithm and studies the effect of hardware design trade-offs on its performance. Our findings based on extensive simulations, which push the reconstruction algorithm to its breaking point, provide important guidelines for the future development of millimetre-sized sensor nodes.
Sensor systems can be deployed in the homes of older adults living alone for functional health assessments. Their information is very useful for health care specialists. The problem lies in developing person independent models while facing a large variability in behavior. We address this problem by, first, proposing a new feature extraction method for data from ambient motion sensors. The method uses functional similarities between houses and daily structure to extract meaningful features. Second, we propose a change-based approach for analyzing data, taking difference scores of both the sensor features and health metrics. To evaluate our approach, experiments on longitudinal data were conducted, where the relationship between sensor data and health measurements was modeled with linear regression and (nonlinear) regression forests. These experiments show that the change-based approach yields better results and that the resulting models can be used as a reliable metric for (functional) health. In addition, feature analysis can help health care specialists understand relevant aspects of behavior. Prediction of health metrics is possible even with simple sensors. With such sensors, it is possible to detect problems and health decline in an early stage. This will have great impact on clinical practice.
An energy harvesting device for obtaining energy from drops without needing of moving the drops along the device, in a reduced scale and combinable with othertypes of harvesting devices, the energy harvesting device comprising one or more triboelectric generators comprising a bottom electrode, a friction or triboelectric element placed over the bottom electrode, and at least two top electrodes placed over the triboelectric element and defining at least one gap between them, exposing the triboelectric element to the external environment so that on contacting a drop of liquid makes an electrical connection between the top electrodes varying the capacitance of the triboelectric generators and alternatively for functioning as a power unit for a sensor or as a self-powered sensor producing an electrical signal generated by the contact of the liquid with the electrodes.
De technische en economische levensduur van auto’s verschilt. Een goed onderhouden auto met dieselmotor uit het bouwjaar 2000 kan technisch perfect functioneren. De economische levensduur van diezelfde auto is echter beperkt bij introductie van strenge milieuzones. Bij de introductie en verplichtstelling van geavanceerde rijtaakondersteunende systemen (ADAS) zien we iets soortgelijks. Hoewel de auto technisch gezien goed functioneert kunnen verouderde software, algorithmes en sensoren leiden tot een beperkte levensduur van de gehele auto. Voorbeelden: - Jeep gehackt: verouderde veiligheidsprotocollen in de software en hardware beperkten de economische levensduur. - Actieve Cruise Control: sensoren/radars van verouderde systemen leiden tot beperkte functionaliteit en gebruikersacceptatie. - Tesla: bij bestaande auto’s worden verouderde sensoren uitgeschakeld waardoor functies uitvallen. In 2019 heeft de EU een verplichting opgelegd aan automobielfabrikanten om 20 nieuwe ADAS in te bouwen in nieuw te ontwikkelen auto’s, ongeacht prijsklasse. De mate waarin deze ADAS de economische levensduur van de auto beperkt is echter nog onvoldoende onderzocht. In deze KIEM wordt dit onderzocht en wordt tevens de parallel getrokken met de mobiele telefonie; beide maken gebruik van moderne sensoren en software. We vergelijken ontwerpeisen van telefoons (levensduur van gemiddeld 2,5 jaar) met de eisen aan moderne ADAS met dezelfde sensoren (levensduur tot 20 jaar). De centrale vraag luidt daarom: Wat is de mogelijke impact van veroudering van ADAS op de economische levensduur van voertuigen en welke lessen kunnen we leren uit de onderliggende ontwerpprincipes van ADAS en Smartphones? De vraag wordt beantwoord door (i) literatuuronderzoek naar de veroudering van ADAS (ii) Interviews met ontwerpers van ADAS, leveranciers van retro-fit systemen en ontwerpers van mobiele telefoons en (iii) vergelijkend rij-onderzoek naar het functioneren van ADAS in auto’s van verschillende leeftijd en prijsklassen.
Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
Various companies in diagnostic testing struggle with the same “valley of death” challenge. In order to further develop their sensing application, they rely on the technological readiness of easy and reproducible read-out systems. Photonic chips can be very sensitive sensors and can be made application-specific when coated with a properly chosen bio-functionalized layer. Here the challenge lies in the optical coupling of the active components (light source and detector) to the (disposable) photonic sensor chip. For the technology to be commercially viable, the price of the disposable photonic sensor chip should be as low as possible. The coupling of light from the source to the photonic sensor chip and back to the detectors requires a positioning accuracy of less than 1 micrometer, which is a tremendous challenge. In this research proposal, we want to investigate which of the six degrees of freedom (three translational and three rotational) are the most crucial when aligning photonic sensor chips with the external active components. Knowing these degrees of freedom and their respective range we can develop and test an automated alignment tool which can realize photonic sensor chip alignment reproducibly and fully autonomously. The consortium with expertise and contributions in the value chain of photonics interfacing, system and mechanical engineering will investigate a two-step solution. This solution comprises a passive pre-alignment step (a mechanical stop determines the position), followed by an active alignment step (an algorithm moves the source to the optimal position with respect to the chip). The results will be integrated into a demonstrator that performs an automated procedure that aligns a passive photonic chip with a terminal that contains the active components. The demonstrator is successful if adequate optical coupling of the passive photonic chip with the external active components is realized fully automatically, without the need of operator intervention.
