The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Cooperative transportation system for humanoid robots using simulation-based learning
Applied Soft Computing
Pedestrian localisation for indoor environments
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Navitime: Supporting Pedestrian Navigation in the Real World
IEEE Pervasive Computing
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Indoor Emergency Evacuation Service on Autonomous Navigation System using Mobile Phone
ISUC '08 Proceedings of the 2008 Second International Symposium on Universal Communication
Zone-based rss reporting for location fingerprinting
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
Place lab: device positioning using radio beacons in the wild
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
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In this paper, we propose a positioning system for indoor pedestrian navigation services using mobile phones. Position information services with a Global Positioning System (GPS) are widely used for car navigation and portable navigation. Their navigation systems facilitate development of industry and increase the convenience of civil life. However, such systems and services are available only for locations in which satellite signals can be received because users' self-positions are computed using GPS. Therefore, we developed a system for indoor environments, operating with a user's mobile terminal and battery-driven beacon devices in a server-less environment. Moreover, to provide convenient services using position information indoors, we developed an indoor navigation system that is useful in commercial facilities and office buildings. The system consists of smart phone and license-free radio beacon devices that can be driven with little electric power. In our proposed method, probabilistic estimation algorithms are applied to estimate self-positions in indoor locations, such as those where it is impossible to receive GPS signals. Feature of the system is that 2.5-dimensional indoor positioning is possible to calculate with low computational power device such as mobile phone. The system works autonomously, i.e., the user's device receives wireless beacon signals from the surrounding environment and can thereby detect a user's position independently from the mobile terminal, thereby obviating server-side computation.