| dc.description.abstract | Applications that adapt to environmental and situational changes are difficult to build because computers cannot capture, represent or process context information as easily as human beings. Nevertheless, context information is very valuable because it allows applications to be made more user-friendly, flexible, and adaptable. This realization has spawned a multitude of research efforts to simplify development of context-sensitive applications. A result of one of these research efforts is the Argos middleware platform, which is an application server created specifically for personal applications that can adapt to changes in their environment.
Applications that rely on context information must often collect this information from external measurement devices, commonly known as sensors. These devices respond directly to physical stimulus to produce meaningful information about their surroundings. Typical examples are sensors that produce location, temperature or motion information, but they can also, for instance, be devices that monitors the physical condition of a person. The goal of this thesis has been to design, develop and evaluate functionality for the Argos middleware platform that makes it easier for Argos applications to collect and use sensor measurements.
The functionality has been developed in collaboration with the National Center for Telemedicine (NST) who wants to use Argos for monitoring patients. They intend to develop a system that can give patients semi-automatic feedback and advice on how to maintain and improve their lifestyle. To do this they want to use personal sensors that monitor attributes relevant to a patient's condition. The functionality developed in this thesis has provided a starting point for NST to develop their system and contributed lots of technical information that will prove useful for their project. | en |
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