Titlebook: Smart Sensing and Context; 4th European Confere Payam Barnaghi,Klaus Moessner,Stefan Meissner Conference proceedings 2009 Springer-Verlag B

态度暖昧

生来

Episode Segmentation Using Recursive Multiple Eigenspacesng their general application to pervasive sensing applications. This paper presents an improved multiple eigenspace segmentation algorithm that addresses the common problem of under-segmentation in episode detection. Results show that the proposed algorithm significantly increases the segmentation accuracy when compared to existing methods.

Melanocytes

有权

Mobile Context Toolboxments 14 participants have been continuously using a Nokia N95 mobile phone with a . application for an average of 48 days per user and covering 70% of the time. The study has provided valuable insights into the performance issues of the system in real-life usage situations, including the stability of and power consumption in the system.

NIB

A Query Service for Raw Sensor Datahe liveSensor system which offers the benefits of an enriched sensor stream, providing a high level query interface to the user. However, it delays the enrichment of sensor data until after query results have been generated and thus, maintains a high level of performance by processing raw sensor streams.

assail

exhilaration

Semantic Annotation and Reasoning for Sensor Data sensor observation and measurement data and linked data to derive additional or approximate knowledge. Furthermore, we discuss the association between sensor data, the semantic Web, and the social Web which enable construction of context-aware applications and services, and contribute to construction of a networked knowledge framework.

allude

Context-Aware Recommendations on Mobile Services: The m:Ciudad Approachironment are taken into consideration and are reflected in the design of the m:Ciudad Search and Recommendation Engine. We discuss how context-awareness and proactivity can be implemented and utilised for mobile services.

天赋

Automatic Event-Based Synchronization of Multimodal Data Streams from Wearable and Ambient Sensorsnization approach. In particular, we show that the event timing relation is transitive for sensor groups with shared members. We analyzed our synchronization approach in three studies. For a large dataset of 5 users and totally 308 data stream minutes we achieved a synchronization error of 0.3 s for more than 80% of the stream.

CESS