Technologies

This technology is an e-health application. The DragONE application is inspired by the global guidelines for the management of asthma, which promote the opportunity to implement a multidimensional assessment of pediatric asthma using innovative systems. DragONE allows to record data on the subjective control of asthma, by using easy-to-understand colors and icons for children (red, yellow or green dragon), to keep track to the patient’s of perceived state.

Our innovative proposal involves an educational robotics training program, resulting from an experimental research that combines traditional educational approaches with the utilization of robotics. Specifically, the educational robot Thymio, developed by EPFL, serves as a facilitator in the learning process to enhance School Readiness.

Plants have a huge potential to contribute to the solution of a large number of issues facing the modern world, ranging from a poor crop yields and problems caused by global climate changing. Our team has been on the forefront of the PCR and NGS applications to plant responses to biotic and abiotic stress. As experts in genomics and plant pathology we are able to accelerate the understanding and use of plant genes and resources.

Quartz tuning forks are employed in scanning atomic force microscopy (AFM), as well as in some derived techniques, as high sensitivity detectors of interactions, of both conservative and dissipative kind, between the AFM nanometric probe and the investigated surface. However, the contributions of the two kinds of interaction result as convoluted in the sensor response, preventing fully quantitative measurements of the quantities of interest.

The platform allows acquisition of data from commercial and custom sensors. By now, the system has been embedded in a wearable wristband where elastomeric based strain gauge have been integrated to detect fine hand/wrist/arm movements. The platform integrates inertial sensors (accelerometers, gyroscopes) to acquire more details about the subject movements. A sensor-fusion algorithm enables advanced movement recognition (gesture, 3D orientation). A machine-learning algorithm is in development to increase the performance of the platform.

The environment as well as the food production provide a number of both natural and synthetic compounds whose effects on human being as an organism have not yet been determined nor investigated.

The prototype uses soil moisture sensors which, through a measurement of dielectric permittivity, estimate the soil moisture based on which irrigation is started through relay-controlled solenoid valve. The system was developed using Open Source technologies. Specifically, for the hardware components, a small sized board computer Raspberry PI 3B + was used together with a 4G LTE Wi-Fi router and a Modbus rs485 / USB converter.

To the enterprises working in the field of nutrition/nutraceutics and drug development/repositioning, we offer the know-how and state-of-the-art instrumentation of our labs to monitor multiple relevant biological parameters at the cellular level: metabolic activity, vitality, health, but also stress and toxicity. The use of advanced imaging techniques based on fluorescent/bioluminescent probes together with the availability of time-lapse acquisitions, guarantee the cutting-edge analysis of different biological parameters over time.

This form describes a programmable, autonomous and stand-alone imaging system for the acquisition and processing of images containing subjects whose size is larger than 1cm (e.g. gelatinous zooplankton, fishes, litter, manufacts), form the seafloor or along the water column, in shallow or deep waters. It is capable to recognize and classify the image content through pattern recognition algorithms that combine computer vision and artificial intelligence methodologies.

Environmental monitoring is a rapidly growing field, both in academia and industry. The use of wearables for environmental monitoring is a promising technique, as it allows data to be collected continuously and comprehensively. The main problem with using wearables for environmental monitoring is the size and weight of the system, as well as the high degree of specialization required to develop a fully functional device.