Philip Kuryloski

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CareNet is an integrated wireless sensor environment for remote healthcare that uses a two-tier wireless network and an extensible software platform. CareNet provides both highly reliable and privacy-aware patient data collection, transmission and access. This paper describes our system architecture, software development, and the results of our field(More)
We present an open-source platform for wireless body sensor networks called DexterNet. The system supports real-time, persistent human monitoring in both indoor and outdoor environments. The platform utilizes a three-layer architecture to control heterogeneous body sensors. The first layer called the body sensor layer (BSL) deals with design of(More)
We propose a distributed recognition method to classify human actions using a low-bandwidth wearable motion sensor network. Given a set of pre-segmented motion sequences as training examples, the algorithm simultaneously segments and classifies human actions, and it also rejects outlying actions that are not in the training set. The classification is(More)
Wireless body sensor networks (BSNs) possess enormous potential for changing people’s daily lives. They can enhance many human-centered application domains such as m-Health, sport and wellness, and human-centered applications that involve physical/virtual social interactions. However, there are still challenging issues that limit their wide diffusion in(More)
SPINE is an Open Source Framework for the design of signal processing intensive (SPI) WSNs. It supports the construction of WSN applications through high-level abstractions and libraries, and allows designers to quickly explore implementation tradeoffs through fast prototyping. This paper describes the architecture of SPINE and presents implementation(More)
Within context-aware computing, there is a growing interest in linking localization technologies with activity recognition in a cooperative way. Existing research works in this field face two main difficulties: lack of accuracy in their solutions and/or sophisticated hardware requirements. To avoid these issues, we present a light-weight, low-cost and(More)
In this paper we propose the integration of computer vision with accelerometry in order to provide a precise localization solution. In terms of accelerometry, our approach makes use of a single off-the-shelf accelerometer on the waist to precisely obtain the velocity of the user. This allows us to calculate the kinetic energy of the person being tracked,(More)
This paper presents ongoing work with a wireless sensor network application at the Herbert Johnson Art Museum. We discuss the design and deployment of networked motes for the purpose of collecting information about museum visitors including number, density and tempo of group movement within the space. We also address the use of the collected data for(More)
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