OPF: A distributed context-sensing framework for ubiquitous computing environments

被引:0
|
作者
Van Kleek, Max
Kunze, Kai
Partridge, Kurt
Begole, James Bo
机构
[1] MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA
[2] Univ Passau, Inst Embedded Syst, D-94032 Passau, Germany
[3] Palo Alto Res Ctr, Palo Alto, CA 94304 USA
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes the Obje Perception Framework (OPF), a distributed software architecture for context sensing and inference in ubiquitous computing environments. OPF provides flexibility, scalability, and robustness even as the sensor configuration changes. For flexibility, OPF supports many context inference tasks, ways of achieving those tasks, and heterogeneity in sensor types. With respect to scalability, OPF accommodates the needs of a large number of applications simultaneously while conserving power and reducing the amount of data transmitted over the network. And to support robustness to dynamism, OPF constructs context inference pipelines to satisfy each applications' needs in a goal-directed fashion. The value of OPF is demonstrated by a case study of an end-user application that helps users establish and manage connections among the various digital resources in their environment.
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页码:82 / 97
页数:16
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