Espositori 2018


Wireless sensors for last meters of Internet of Things In Healthcare and Industry

Wireless sensors for last meters of Internet of Things In Healthcare and Industry

How to transform objects into data generators by means of embedded, batteryless sensors suitable to wireless reading. We have preserved the simplicity of the assessed RadioFrequency IDentification (RFID) while extending its potentiality to the discrete and pervasive monitoring of the environment, the manufacturing chain as well as the health status of the human body.
We will show and demonstrate a complete ecosystem comprising epidermal wireless sensors for the application over the human skin to measure biophysical parameters and to restore the lost senses of touch. We will also show sensors suitable to monitor infrastructures and the manufacturing of products for Industry 4.0, and flying sensors (nano Tag-Copters) for the volumetric data collection.
Italy

Wireless sensors for last meters of Internet of Things In Healthcare and Industry

The Pervasive Electromagnetic Lab & Radio6ense: Gaetano Marrocco, Cecilia Occhiuzzi, Sara Amendola, Simone Nappi, Nicola D'Uva, Carolina Miozzi, Michela Longhi

Ref. Prof. Gaetano Marrocco
Full professors of Electromagnetics at the University of Roma Tor Vergata. Chair of the Pervasive Electromagnetics Lab. Since 2002 he is carrying on pioneering research in the emerging topic of Radiofrequency Identification and he is contributing to the development of sensor-oriented RFID systems for application to the Internet of Things and to the bio-integrated epidermal sensors. In particular, his lab developed and experimented the first battery-less RF sensors for deformation, temperature, humidity, gasses, implanted bio prosthesis, and human motion detection and classification, recovering of tactile feeling.
Prof. Marrocco is the co-founder and President of the University spin-off RADIO6ENSE (www.radio6ense.com) active in the short-range electromagnetic sensing for Automotive, Cyber and Physical Security and Structural Health Monitoring.


  A1 (pav. 5) - Università degli Studi di Roma "Tor Vergata"
 2018

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Dati aggiornati il 08/11/2022 - 10.59.34