RFID Sensor-Tags Feeding a Context-Aware Rule-Based Healthcare Monitoring System

  • Authors:

  • Luca Catarinucci;Riccardo Colella;Alessandra Esposito;Luciano Tarricone;Marco Zappatore

  • Affiliations:

  • Department of Engineering for Innovation, University of Salento, Lecce, Italy;Department of Engineering for Innovation, University of Salento, Lecce, Italy;Department of Engineering for Innovation, University of Salento, Lecce, Italy;Department of Engineering for Innovation, University of Salento, Lecce, Italy;Department of Engineering for Innovation, University of Salento, Lecce, Italy

  • Venue:
  • Journal of Medical Systems
  • Year:
  • 2012

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Abstract

Along with the growing of the aging population and the necessity of efficient wellness systems, there is a mounting demand for new technological solutions able to support remote and proactive healthcare. An answer to this need could be provided by the joint use of the emerging Radio Frequency Identification (RFID) technologies and advanced software choices. This paper presents a proposal for a context-aware infrastructure for ubiquitous and pervasive monitoring of heterogeneous healthcare-related scenarios, fed by RFID-based wireless sensors nodes. The software framework is based on a general purpose architecture exploiting three key implementation choices: ontology representation, multi-agent paradigm and rule-based logic. From the hardware point of view, the sensing and gathering of context-data is demanded to a new Enhanced RFID Sensor-Tag. This new device, de facto, makes possible the easy integration between RFID and generic sensors, guaranteeing flexibility and preserving the benefits in terms of simplicity of use and low cost of UHF RFID technology. The system is very efficient and versatile and its customization to new scenarios requires a very reduced effort, substantially limited to the update/extension of the ontology codification. Its effectiveness is demonstrated by reporting both customization effort and performance results obtained from validation in two different healthcare monitoring contexts.