Abstract

In this paper we treat design philosophies and enabling technologies for ambient awareness within grids of future mobile computing/communication devices. We extensively describe the possible context sensors, their required accuracies, their use in mobile services—possibly leading to background interactions of user devices—as well as a draft of their integration into an ambient aware device. We elaborate on position sensing as one of the main aspects of context aware systems. We first describe a maximum accuracy setup for a mobile user that has the ability of Augmented Reality for indoor and outdoor applications. We then focus on a set-up for pose sensing of a mobile user, based on the fusion of several inertia sensors and DGPS. We describe the anchoring of the position of the user by using visual tracking, using a camera and image processing. We describe our experimental set-up with a background process that, once initiated by the DGPS system, continuously looks in the image for visual clues and—when found—tries to track them, to continuously adjust the inertial sensor system. We present some results of our combined inertia tracking and visual tracking system; we are able to track device rotation and position with an update rate of 10 ms with an accuracy for the rotation of about two degrees, whereas head position accuracy is in the order of a few cm at a visual clue distance of less than 3 m.

Author Keywords: Ambient aware devices; Personal digital assistants; Differential global positioning system; UMTS; Ad-hex networking

Article Outline

1. Introduction

2. Ambient awareness in mobile communications

2.1. Ambient awareness

2.2. Context sensors

2.3. Required accuracies for some context based services

2.4. Mapping sensors on services

2.5. Implementing a device with ambient awareness

3. Position sensing

3.1. The maximum set-up: augmented reality

3.2. Position sensing for context awareness

3.3. Position sensing approach

3.4. Position sensing hardware

3.5. Sensor fusion and filtering

4. Position anchoring by using visual tracking

4.1. An experimental camera set-up

4.2. Global search

4.3. Local search

4.4. Calibration and experiments

5. Conclusions

Acknowledgements

References

Vitae

Corresponding author