Title
Engineering Ambient Intelligence Services by Means of MABS
Abstract
In this work, the methodology AmISim to test and to deployment of Ambient Intelligence (AmI) system is presented. The development of AmI systems is a complex task because this technology must adapt to users and contextual information as well as unpredictable and changeable behaviours. So, we focused in how the methodology AmISim can help to the engineering of adaptative services for users. In this case, we propose a predictor of location based on Hidden Markov Models (HMMs). So, the system can offer Location-Based Services(LBS) that adapt to the users. To this end, we propose a methodology based on a previous social multi-agent based simulation (MABS) and a following deployment of the service in a real environment.
Year
DOI
Venue
2010
10.1007/978-3-642-12433-4_5
TRENDS IN PRACTICAL APPLICATIONS OF AGENTS AND MULTIAGENT SYSTEMS
Keywords
Field
DocType
ambient intelligence,location based service,hidden markov model
Contextual information,Software deployment,Ambient intelligence,Computer science,Artificial intelligence,Ubiquitous computing,Hidden Markov model,Machine learning
Conference
Volume
ISSN
Citations 
71
1867-5662
4
PageRank 
References 
Authors
0.41
2
4