Data Fusion from Sensors for Context-aware, Healthcare-management Systems

Information and communication technology (ICT) plays an essential role in supporting daily life in today's digital society. Used everywhere, ICT is now becoming essential to delivering better and more efficient healthcare services. Data come from several separate medical devices, from sensors located near the patient that provide environmental data, from electronic medical records stored by the hospital, from hospital administrative records, and from financial and healthcare resource management. There has been growing interest in multi-disciplinary research on multi-sensor, data-fusion technology, driven by its versatility and diverse areas of application. Therefore, there seems to be a real need for context-aware development in the data-fusion domain. However, different sensors may use different physical principles, cover different information space, and generate data in different formats at different update rates. Sensor-generated information may also have different resolution, accuracy, and reliability properties. Cooperation is vital because e-health systems must be secure and interoperable in order to foster collaboration among healthcare actors (professionals, organizations, patients, etc.). National and local policy-makers and stakeholders must cooperate in order to resolve the various associated legal, organizational and policy issues. In this proposal, we extend the event-driven approach based on interoperable and secure command-query responsibility segregation (CQRS) to define and implement event data based on a general publish-subscribe model. This allows evaluation based on sensor-fusion solutions for a wide range of context-aware computing applications.