Anthony Marcus

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This paper details the architecture and describes the preliminary experimentation with the proposed framework for anomaly detection in medical wireless body area networks for ubiquitous patient and healthcare monitoring. The architecture integrates novel data mining and machine learning algorithms with modern sensor fusion techniques. Knowing wireless(More)
—Wireless Sensor Networks are vulnerable to a plethora of different fault types and external attacks after their deployment. We focus on sensor networks used in healthcare applications for vital sign collection from remotely monitored patients. These types of personal area networks must be robust and resilient to sensor failures as their capabilities(More)
This paper presents a REST-compliant service oriented architecture of a web-based heterogeneous wireless sensor network monitoring system that has applicability in remote patient monitoring in healthcare. As smartphone and web-page technologies are ubiquitous nowadays, our architecture uses smartphone as a gateway between the data collected and the(More)
— Various implementations of wireless sensor networks (i.e. personal area-, wireless body area-networks) are prone to node and network failures by such characteristics as limited node energy resources and hardware damage incurred from their surrounding environment (i.e. flooding, forest fires, a patient falling). This may jeopardize their reliability to act(More)