Authors:
Iuliana Marin
;
Maria Iuliana Bocicor
and
Arthur-Jozsef Molnar
Affiliation:
SC Info World SRL, Bucharest and Romania
Keyword(s):
Indoor Localization, Received Signal Strength, Trilateration, Kalman Filtering, Neural Network.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Cloud Computing
;
Data Engineering
;
Databases and Data Security
Abstract:
This paper presents the initial results of our experiments regarding accurate indoor localisation. The research was carried out in the context of a European Union funded project targeting the development of a configurable, cost-effective cyber-physical system for monitoring older adults in their homes. The system comprises a number of hardware nodes deployed as intelligent luminaires that replace light bulbs present in the monitored location. By measuring the strength of a Bluetooth Low Energy signal generated by a device on the monitored person, a rough estimation of the person’s location is obtained. We show that the presence of walls, furniture and other objects in typical indoor settings precludes accurate localisation. In order to improve accuracy, we employ several software-based approaches, including Kalman filtering and neural networks. We carry out an initial experiment showing that additional software processing significantly improves localisation accuracy.