Gerald Stanje

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This article focuses on a new type of wireless devices in the domain between RFIDs and sensor networks—Energy-Harvesting Active Networked Tags (EnHANTs). Future EnHANTs will be small, flexible, and self-powered devices that can be attached to objects that are traditionally not networked (e.g., books, furniture, toys, produce, and clothing). Therefore,(More)
This paper focuses on a new type of wireless devices in the domain between RFIDs and sensor networks – Energy Harvesting Active Networked Tags (EnHANTs). Future EnHANTs will be small, flexible, and self-powered devices that can be attached to objects that are traditionally not networked (e.g., books, toys, clothing), thereby providing the infrastructure for(More)
Energy Harvesting Active Networked Tags (EnHANTs) are a new class of devices in the domain between RFIDs and sensor networks. EnHANTs will be small, flexible, and energetically self-reliant. Their development is enabled by advances in ultra-low-power ultra-wideband (UWB) communications and in organic semiconductor-based energy harvesting materials. In this(More)
<i>Energy Harvesting Active Networked Tags (EnHANTs)</i> will be a new class of devices in the domain between RFIDs and sensor networks. Small, flexible, and energetically self-reliant, EnHANTs will be attached to objects that are traditionally not networked, such as books, furniture, toys, produce, and clothing. More information about the EnHANTs project(More)
This paper discusses a mixed method that combines unsupervised learning methods and human expert input for analyzing telemetry data from long-duration robotic space missions. Our goal is to develop more automated methods for detecting anomalies in time series data. Once anomalies are identified using unsupervised learning methods we use feature selection(More)
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