Authors:
Marco Paiva
;
Marcelo Petry
and
Rosaldo J. F. Rossetti
Affiliation:
Univeristy of Porto, Portugal
Keyword(s):
Indoor Localization, Local Positioning Systems, Topology Mapping.
Related
Ontology
Subjects/Areas/Topics:
Ambient Intelligence
;
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Formal Methods
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Machine Learning
;
Planning and Scheduling
;
Simulation and Modeling
;
Soft Computing
;
Symbolic Systems
Abstract:
Nowadays location systems are used within a large variety of applications. The application of these systems within indoor environments is already provided by several solutions. However, the need for high accuracy within these environments to pursue such purpose implies the use of specific infrastructures designed towards it. Our project tries to meet the requirements for a simple, low-cost, and scalable location system through different approaches. The main idea of it is to re-construct topological maps of indoor spaces through location estimation, i.e. using off-the-shelf technologies. We try to perform location estimations and then re-create the indoor maps as topological maps as a means of reducing the precision requirements other systems have, and develop a scalable and highly applicable system using sensors featuring mobile devices.