Ambient Intelligence Framework for Context Aware Adaptive Applications

2006 ◽  
Author(s):  
G. Acampora ◽  
V. Loia ◽  
M. Nappi ◽  
S. Ricciardi
Keyword(s):  
Ambient Intelligence ◽  
Context Aware ◽  
Adaptive Applications

CAFCLA

2015 ◽  
pp. 187-209 ◽  
Author(s):  
Óscar García ◽  
Ricardo S. Alonso ◽  
Dante I. Tapia ◽  
Juan M. Corchado
Keyword(s):  
Information And Communication Technologies ◽  
Ambient Intelligence ◽  
Communication Technologies ◽  
Agent Technology ◽  
Learning Approach ◽  
Context Aware ◽  
Computer Supported Collaborative Learning ◽  
Wide Range ◽  
Information And Communication ◽  
Multi Agent

Ambient Intelligence (AmI) promotes the integration of Information and Communication Technologies (ICT) in daily life in order to ease the execution of everyday tasks. In this sense, education becomes a field where AmI can improve the learning process by means of context-aware technologies. However, it is necessary to develop new tools that can be adapted to a wide range of technologies and application scenarios. Here is where Agent Technology can demonstrate its potential. This chapter presents CAFCLA, a multi-agent framework that allows developing learning applications based on the pedagogical CSCL (Computer-Supported Collaborative Learning) approach and the Ambient Intelligence paradigm. CAFCLA integrates different context-aware technologies so that learning applications designed, developed, and deployed upon it are dynamic, adaptive, and easy to use by users such as students and teachers.

SYLPH

2011 ◽  
Vol 3 (2) ◽  
pp. 1-15 ◽  
Author(s):  
Ricardo S. Alonso ◽  
Dante I. Tapia ◽  
Juan M. Corchado
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ambient Intelligence ◽  
Wireless Sensor ◽  
Context Aware ◽  
Preliminary Results ◽  
Ubiquitous Systems ◽  
Heterogeneous Wireless Sensor Networks ◽  
Innovative Solutions ◽  
Flexible Applications

The significance that Ambient Intelligence (AmI) has acquired in recent years requires the development of innovative solutions. In this sense, the development of AmI-based systems requires the creation of increasingly complex and flexible applications. The use of context-aware technologies is an essential aspect in these developments in order to perceive stimuli from the context and react upon it autonomously. This paper presents SYLPH, a novel platform that defines a method for integrating dynamic and self-adaptable heterogeneous Wireless Sensor Networks (WSN). This approach facilitates the inclusion of context-aware capabilities when developing intelligent ubiquitous systems, where functionalities can communicate in a distributed way. A WSN infrastructure has been deployed for testing and evaluating this platform. Preliminary results and conclusions are presented in this paper.

scholarly journals ContextErlang: A language for distributed context-aware self-adaptive applications

2015 ◽  
Vol 102 ◽  
pp. 20-43 ◽  
Author(s):  
Guido Salvaneschi ◽  
Carlo Ghezzi ◽  
Matteo Pradella
Keyword(s):  
Context Aware ◽  
Adaptive Applications ◽  
Self Adaptive

RecAm: a collaborative context-aware framework for multimedia recommendations in an ambient intelligence environment

2015 ◽  
Vol 22 (5) ◽  
pp. 587-601 ◽  
Author(s):  
Mohammed F. Alhamid ◽  
Majdi Rawashdeh ◽  
Haiwei Dong ◽  
M. Anwar Hossain ◽  
Abdulhameed Alelaiwi ◽  
...  
Keyword(s):  
Ambient Intelligence ◽  
Context Aware ◽  
Collaborative Context

scholarly journals Improving an Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care using Wireless Sensor Networks

2011 ◽  
pp. 17-30
Author(s):  
Dante I. Tapia ◽  
Ricardo S. Alonso ◽  
Juan M. Corchado
Keyword(s):  
Health Care ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ambient Intelligence ◽  
Wireless Sensor ◽  
Context Aware ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

This paper describes last improvements made on ALZ-MAS; an Ambient Intelligence based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients. The system makes use of several context-aware technologies that allow it to automatically obtain information from users and the environment in an evenly distributed way, focusing on the characteristics of ubiquity, awareness, intelligence, mobility, etc., all of which are concepts defined by Ambient Intelligence. Among these context-aware technologies we have Wireless Sensor Networks. In this sense, ALZ-MAS is currently being improved by the use of a new platform of ZigBee devices that provides the system with new telemonitoring and locating engines.

SYLPH

2014 ◽  
pp. 58-72
Author(s):  
Ricardo S. Alonso ◽  
Dante I. Tapia ◽  
Juan M. Corchado
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ambient Intelligence ◽  
Wireless Sensor ◽  
Context Aware ◽  
Preliminary Results ◽  
Ubiquitous Systems ◽  
Heterogeneous Wireless Sensor Networks ◽  
Innovative Solutions ◽  
Flexible Applications

The significance that Ambient Intelligence (AmI) has acquired in recent years requires the development of innovative solutions. In this sense, the development of AmI-based systems requires the creation of increasingly complex and flexible applications. The use of context-aware technologies is an essential aspect in these developments in order to perceive stimuli from the context and react upon it autonomously. This paper presents SYLPH, a novel platform that defines a method for integrating dynamic and self-adaptable heterogeneous Wireless Sensor Networks (WSN). This approach facilitates the inclusion of context-aware capabilities when developing intelligent ubiquitous systems, where functionalities can communicate in a distributed way. A WSN infrastructure has been deployed for testing and evaluating this platform. Preliminary results and conclusions are presented in this paper.

Context-Aware Adaptive Applications: Fault Patterns and Their Automated Identification

2010 ◽  
Vol 36 (5) ◽  
pp. 644-661 ◽  
Author(s):  
Michele Sama ◽  
Sebastian Elbaum ◽  
Franco Raimondi ◽  
David S. Rosenblum ◽  
Zhimin Wang
Keyword(s):  
Context Aware ◽  
Automated Identification ◽  
Adaptive Applications
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