Design and Manufacture of Flexible Epidermal NFC Device for Electrochemical Sensing of Sweat

Flexible and epidermal sensing devices are becoming vital to enable precision medicine and telemonitoring systems. The NFC (Near Field Communication) protocol is also becoming increasingly important for this application since it is embedded in most smartphones that can be used as pervasive and low-cost readers. Furthermore, the responder can be passive and can harvest enough power to perform electromagnetic sensing. Finally, the NFC coils are robust to bending and to the human body's presence. This contribution details the design of a new flexible device, including an electrochemical sensor communicating through the NFC protocol. A spiral NFC antenna is designed, and a manufactured prototype is experimentally tested to quantify the robustness to the inter-wearer variability and the bending. Lastly, the sensory data retrieval is validated by comparison with a portable potentiostat. The realized sensor can be comfortably worn and be easily read by smartphones independently from the wearer and from the point of application and could be used in future for estimating the user's psycho-physical health by analyzing the body's sweat.

Automatic Monitoring of Fruit Ripening Rooms by UHF RFID Sensor Network and Machine Learning

Accelerated ripening through the exposure of fruits to controlled environmental conditions and gases is nowadays one of the most assessed food technologies, especially for climacteric and exotic products. However, a fine granularity control of the process and consequently of the quality of the goods is still missing, so the management of the ripening rooms is mainly based on qualitative estimations only. Following the modern paradigms of Industry 4.0, this contribution proposes a non-destructive RFID-based system for the automatic evaluation of the live ripening of avocados. The system, coupled with a properly trained automatic classification algorithm based on Support Vector Machines (SVMs), can discriminate the stage of ripening with an accuracy greater than 85%.