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Journal ArticleDOI

The Gator Tech Smart House: a programmable pervasive space

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TLDR
The University of Florida's Mobile and Pervasive Computing Laboratory is developing programmable pervasive spaces in which a smart space exists as both a runtime environment and a software library.
Abstract
Research groups in both academia and industry have developed prototype systems to demonstrate the benefits of pervasive computing in various application domains. Unfortunately, many first-generation pervasive computing systems lack the ability to evolve as new technologies emerge or as an application domain matures. To address this limitation, the University of Florida's Mobile and Pervasive Computing Laboratory is developing programmable pervasive spaces in which a smart space exists as both a runtime environment and a software library. Service discovery and gateway protocols automatically integrate system components using generic middleware that maintains a service definition for each sensor and actuator in the space. The Gator Tech Smart House in Gainesville, Florida, is the culmination of more than five years of research in pervasive and mobile computing. The project's goal is to create assistive environments such as homes that can sense themselves and their residents and enact mappings between the physical world and remote monitoring and intervention services.

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Citations
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A Survey on Ambient-Assisted Living Tools for Older Adults

TL;DR: The emergence of `ambient-assisted living’ (AAL) tools for older adults based on ambient intelligence paradigm is summarized and the state-of-the-art AAL technologies, tools, and techniques are summarized.
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Sensor-Based Activity Recognition

TL;DR: A comprehensive survey to examine the development and current status of various aspects of sensor-based activity recognition, making a primary distinction in this paper between data-driven and knowledge-driven approaches.
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A review of smart homes-Present state and future challenges

TL;DR: This article presents an international selection of leading smart home projects, as well as the associated technologies of wearable/implantable monitoring systems and assistive robotics, often designed as components of the larger smart home environment.
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Review: Ambient intelligence: Technologies, applications, and opportunities

TL;DR: This paper provides a survey of the technologies that comprise ambient intelligence and of the applications that are dramatically affected by it and specifically focuses on the research that makes AmI technologies ''intelligent''.
Proceedings ArticleDOI

Accurate activity recognition in a home setting

TL;DR: This paper presents an easy to install sensor network and an accurate but inexpensive annotation method and shows how the hidden Markov model and conditional random fields perform in recognizing activities.
References
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Journal ArticleDOI

Understanding and Using Context

TL;DR: An operational definition of context is provided and the different ways in which context can be used by context-aware applications are discussed, including the features and abstractions in the toolkit that make the task of building applications easier.
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Location systems for ubiquitous computing

TL;DR: This survey and taxonomy of location systems for mobile-computing applications describes a spectrum of current products and explores the latest in the field to help developers of location-aware applications better evaluate their options when choosing a location-sensing system.

A Survey of Context-Aware Mobile Computing Research

TL;DR: This survey of research on context-aware systems and applications looked in depth at the types of context used and models of context information, at systems that support collecting and disseminating context, and at applications that adapt to the changing context.
Proceedings ArticleDOI

The smart floor: a mechanism for natural user identification and tracking

TL;DR: A system for identifying people based on their footstep force profiles and its accuracy against a large pool of footstep data is tested and it is shown that the effect of footwear is negligible on recognition accuracy.
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