The idea is to develop new RFID smart tag sensors to be used in a monitoring service assisted by ICT platform to monitor fresh produce quality. It is based on a smart gas sensor and consists of a commercial fork of open hardware, on which we assembly an array of commercial sensors suitable for air quality monitoring. In particular, to measure ethylene (ripening marker) a class of unspecific metal oxide commercial sensors has been selected and tested, in controlled environment, to probe the response capability to extremely low gas concentration (less than tens ppm). Firmware implemented uses a power management strategy to minimize device consumption. It is able to save locally raw data and transmit, on request, an index correlated to the vegetable ripening. The index results from a mathematical model based on time-integral function depending on the vegetable transport parameters, temperature, humidity and gas sensor outputs. Work in progress deals to optimize the algorithm and mathematical model implemented in device with Onsite experimentation. © 2014 IEEE.
RFID tag for vegetable ripening evaluation using an auxiliary smart gas sensor
Di Francia, G.;Buonanno, Antonio.;De Vito, S.;Massera, E.;Formisano, F.
2014-01-01
Abstract
The idea is to develop new RFID smart tag sensors to be used in a monitoring service assisted by ICT platform to monitor fresh produce quality. It is based on a smart gas sensor and consists of a commercial fork of open hardware, on which we assembly an array of commercial sensors suitable for air quality monitoring. In particular, to measure ethylene (ripening marker) a class of unspecific metal oxide commercial sensors has been selected and tested, in controlled environment, to probe the response capability to extremely low gas concentration (less than tens ppm). Firmware implemented uses a power management strategy to minimize device consumption. It is able to save locally raw data and transmit, on request, an index correlated to the vegetable ripening. The index results from a mathematical model based on time-integral function depending on the vegetable transport parameters, temperature, humidity and gas sensor outputs. Work in progress deals to optimize the algorithm and mathematical model implemented in device with Onsite experimentation. © 2014 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
