Context Awareness for Mobile Sensing Introduction Context Awareness Essentials Contextual Information Context Representation ContextModeling Context-Aware Middleware Context Inference Context-Aware Framework Designs Context-Aware Applications Health Care andWell-Being Based Human Activity Recognition Based Transportation and Location Based Social Networking Based Environmental Based Challenges and Future Trends Energy Awareness Adaptive and Opportunistic Sensory Sampling Modeling the Smart Device Battery Behavior for Energy Optimizations Data Calibration and Robustness Efficient Context Inference Algorithms Generic Context-Aware Framework Designs Standard Context-Aware Middleware Solutions Mobile Cloud Computing Security, Privacy, and Trust Context Inference: Posture Detection Discussions Proposed Classification Method Standalone Mode Assisting Mode Feature Extraction Pattern Recognition¿Based Classification Gaussian Mixture Model k -Nearest Neighbors Search Linear Discriminant Analysis Online Processing: Dynamic Training Statistical Tool¿Based Classification Performance Evaluation Context-Aware Framework: A Basic Design Discussions Proposed Framework Preliminaries User State Representation System Adaptability Time-Variant User State Transition Matrix Time-Variant Observation Emission Matrix Update on System Parameters Entropy Rate Scaling Problem Simulations Preparations Applied Process Power Consumption Model Accuracy Model Parameter Setups Results and Discussions Validation by a Smartphone Application Observation Analysis Construction of Observation Emission Matrix Applied Process Performance Evaluation Energy Efficiency in Physical Hardware Discussions Battery Modeling Modeling of Energy Consumption by Sensors Preliminaries Modeling of Sensory Operations Validation by a Smartphone Application Sensor Management Battery Case Sensor Utilization Case Performance Analysis Method I (MI) Method II (MII) Method III (MIII) Context-Aware Framework: A Complex Design Proposed Framework Context Inference Module Inhomogeneous Statistical Machine Basic Definitions and Inhomogeneity Underlying Process User State Representation Time-Variant User State TransitionMatrix Adaptive Observation Emission Matrix Accuracy Notifier and Definition of Actions Sensor Management Module Sensor Utilization Trade-Off Analysis Intuitive Solutions Method I (MI) Method II (MII) Method III (MIII) Constrained Markov Decision Process¿Based Solution Partially Observable Markov Decision Process¿Based Solution Myopic Strategy and Sufficient Statistics Performance Evaluation Probabilistic Context Modeling Construction of Hidden Markov Models General Model Parallel HMMs Factorial HMMs Coupled/Joint HMMs Observation Decomposed/Multiple Observation HMMs Hierarchical HMMs Dynamic Bayesian Networks Evaluation Inference Learning: Forward¿Backward Procedure Extended Forward¿Backward Procedure Model for Multiple Sensors Use Appendix References Index.