Authors:
Bolívar Silva
1
;
João Carlos Lima
1
;
Celio Trois
1
;
William Pereira
1
and
Cristiano da Rocha
2
Affiliations:
1
Universidade Federal de Santa Maria, Av. Roraima no 1000, Santa Maria, Rio Grande do Sul and Brazil
;
2
Penguin Formula, Lisbon and Portugal
Keyword(s):
Indoor Positioning, Opportunistic Wi-Fi Sensing, Object Detection, Pervasive Computing, Location based Service.
Related
Ontology
Subjects/Areas/Topics:
Data Communication Networking
;
Enterprise Information Systems
;
Internet of Things
;
Sensor Networks
;
Software Agents and Internet Computing
;
Software and Architectures
;
Telecommunications
;
Ubiquitous Computing
;
Wireless and Mobile Computing
;
Wireless and Mobile Technologies
;
Wireless Information Networks and Systems
Abstract:
The popularization of mobile devices and increasing the number of sensors and embedded resources boosted a large amount of research in the area of context-aware. Among the most relevant contextual information is the location. In outdoor environments, the GPS technology is already widespread and used. However, the people tend to spend most of their time indoors, such as universities, hospitals, malls, and supermarkets, where the GPS location is compromised. Several approaches using mainly radio frequency technologies have been proposed to solve the problem of indoor location. So far, no widely accepted solution solves the problem of location indoors. In this way, this work to use an opportunistic approach, making use of the Wi-Fi infrastructure available in the environment, to provide the location of mobile stations. Based on this objective, the WALDO architecture was developed that unites the characteristics of different approaches of the works that have been produced in recent years
, taking into account the techniques that present better results at each stage, in conjunction with a zone-based approach and ranking, on phase online of the fingerprint technique, which makes ignoring RSS readings that present noises.
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