Semantics in mobile sensing
By: Zhixian Yan, Dipanjan Chakraborty
Contributors: Chakraborty, Dipanjan, author
Series: Synthesis lectures on the semantic web, theory and technology -- #8; Synthesis lectures on the semantic web, theory and technology -- #8.
Publisher: Morgan & Claypool Publishers
Published: 2014
Place of publication: San Rafael, California]
Language: eng
Number of pages: 131
ISBN-13: 9781627053914; 9781627053907
Subjects: Mobile computing; Sensor networks; Smartphones; COMPUTERS; Computer Literacy; Computer Science; Data Processing; Hardware; General; Information Technology; Machine Theory; Reference
Description: The dramatic progress of smartphone technologies has ushered in a new era of mobile sensing, where traditional wearable on-body sensors are being rapidly superseded by various embedded sensors in our smartphones. For example, a typical smartphone today, has at the very least a GPS, WiFi, Bluetooth, triaxial accelerometer, and gyroscope. Alongside, new accessories are emerging such as proximity, magnetometer, barometer, temperature, and pressure sensors. Even the default microphone can act as an acoustic sensor to track noise exposure for example. These sensors act as a 'lens' to understand the user' context along different dimensions.
Notes: Includes bibliographical references (pages 115-129).
Table of contents: title: 1. Introduction; title: 1.1 Mobile sensing: definitions and scope; title: 1.1.1 Smartphone-based sensing; title: 1.1.2 Sensing architectures; title: 1.2 Semantics from sensors; title: 1.2.1 Semantic modeling of mobile sensors; title: 1.2.2 Semantic computation from mobile sensors; title: 1.3 Book structure.; title: 2. Semantic trajectories from positioning sensors; title: 2.1 The positioning sensor; title: 2.1.1 Sensor type and functionality; title: 2.1.2 Dealing with positioning data: technical summary; title: 2.1.3 From GPS to semantic trajectories; title: 2.2 Semantic trajectory modeling; title: 2.2.1 Semantic trajectory ontology; title: 2.2.2 Hybrid semantic trajectory model; title: 2.3 Semantic trajectory computation; title: 2.3.1 Data preprocessing layer; title: 2.3.2 Trajectory identification layer; title: 2.3.3 Trajectory structure layer; title: 2.4 Semantic trajectory annotation; title: 2.4.1 Annotation with semantic regions; title: 2.4.2 Annotation with semantic lines; title: 2.4.3 Annotation with semantic points; title: 2.5 Summary and outlook.; title: 3. Semantic activities from motion sensors; title: 3.1 The motion sensor; title: 3.1.1 Sensor functionality; title: 3.1.2 What can we learn from motion?; title: 3.1.3 Data collection; title: 3.2 Feature spaces; title: 3.2.1 Data processing; title: 3.2.2 Feature classes, an overview; title: 3.2.3 Feature computation and energy; title: 3.3 Activity learning techniques; title: 3.3.1 Learning models; title: 3.3.2 Choice of learning models; title: 3.3.3 Testing; title: 3.4 Case study: micro activity (MA) learning; title: 3.4.1 Data collection; title: 3.4.2 Feature vector representation; title: 3.4.3 Results of MA supervised learning; title: 3.5 Case study: complex activity learning; title: 3.5.1 User recruitment and data collection; title: 3.5.2 Data processing & sanitization; title: 3.5.3 Features for complex activities; title: 3.5.4 Complex activity learning approaches; title: 3.5.5 Learning performance; title: 3.6 Conclusions and summary.; title: 4. Energy-efficient computation of semantics from sensors; title: 4.1 Energy-efficient mobile sensing; title: 4.1.1 Smartphone battery limitations; title: 4.1.2 Energy-efficient sensing: hardware approaches; title: 4.1.3 Energy-efficient sensing: software approaches; title: 4.2 Model-based energy-efficient sensing; title: 4.2.1 Two-tier optimal sensing; title: 4.2.2 Model-based optimal segmentation; title: 4.2.3 Model-based optimal sensor sampling; title: 4.3 Energy-efficient semantic activity learning; title: 4.3.1 Classification accuracy vs. energy consumption; title: 4.3.2 A3R, a methodology for continuous adaptive sampling; title: 4.4 Concluding remarks.; title: 5. Conclusion; title: 5.1 Summary; title: 5.2 Challenges and opportunities; title: Bibliography; title: Authors' biographies.