Methods for Online Management of AmI Capabilities Relative to Users’ Goals 1st edition by Ittai Flascher, Robert Shaw, Claire Michaels, Oded Flascher ISBN 3540204183 9783540204183
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Authors:Ittai Flascher, Robert E. Shaw, Claire F. Michaels; Oded M. Flascher , Tags:Ambient Intelligence , Author sort:Ittai Flascher, Robert E. Shaw, Claire F. Michaels & Flascher, Oded M. , Languages:Languages:eng , Published:Published:Sep 2003
Methods for Online Management of AmI Capabilities Relative to Users’ Goals 1st edition by Ittai Flascher, Robert E. Shaw, Claire F. Michaels, Oded M. Flascher – Ebook PDF Instant Download/Delivery. 3540204183, 978-3540204183
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Product details:
ISBN 10: 3540204183
ISBN 13: 978-3540204183
Author: Ittai Flascher, Robert E. Shaw, Claire F. Michaels, Oded M. Flascher
Managing the various capabilities of computing environments to best support users’ goals has proven a difficult problem in transportation systems and hand-held devices. In the case of mobile users, the goal of safe and efficient navigation is a persistent part of the users’ context and therefore in the online decisions on what information and services to provide. We present a feasibility test of general methods for measuring and predicting actors’ goal-directed performance, and outline their use in effecting decisions with regard to initiating and halting interactions with users, anticipation of users’ needs, and the evaluation of Ambient Intelligence designs.
Methods for Online Management of AmI Capabilities Relative to Users’ Goals 1st Table of contents:
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Introduction
- 1.1 Background and Motivation
- 1.2 Objective of the Paper
- 1.3 Scope and Contributions
- 1.4 Structure of the Paper
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Related Work
- 2.1 Ambient Intelligence (AmI) Systems and Capabilities
- 2.2 User Goals in Intelligent Environments
- 2.3 Online Management and Adaptation in AmI Systems
- 2.4 Existing Approaches for Goal-Oriented AmI Systems
- 2.5 Challenges in Dynamic Management of AmI Capabilities
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Fundamentals of Online Management in Ambient Intelligence
- 3.1 Definition and Characteristics of Ambient Intelligence
- 3.2 Key Capabilities of AmI Systems (Sensors, Actuators, Data Processing)
- 3.3 Real-Time Adaptation and Personalization
- 3.4 User Goals and Intentions in Intelligent Environments
- 3.5 Interactivity and Responsiveness in AmI Systems
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Goal Modeling and Representation
- 4.1 Framework for Defining User Goals in AmI Environments
- 4.2 Modeling User Intentions and Preferences
- 4.3 Goal Hierarchy and Decomposition
- 4.4 Dynamic and Evolving Goal Representation
- 4.5 Tools for Monitoring and Updating User Goals
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Methods for Online Management of AmI Capabilities
- 5.1 Real-Time Tracking and Monitoring of User Behavior
- 5.2 Context-Aware Decision-Making for Goal Fulfillment
- 5.3 Adaptive Resource Allocation in AmI Systems
- 5.4 User-Centric Dynamic Management Strategies
- 5.5 Optimization of System Capabilities for Goal Alignment
- 5.6 Integration with IoT and Smart Devices
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Personalization and Adaptation Techniques
- 6.1 Personalization of AmI System Responses
- 6.2 Machine Learning Approaches for Goal Prediction and Adaptation
- 6.3 User Profiling and Feedback Loops
- 6.4 Context-Aware Adaptation Mechanisms
- 6.5 Behavioral Adaptation Based on Sensor Data and User Feedback
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Evaluation of Online Management Methods
- 7.1 Metrics for Evaluating the Effectiveness of Goal-Oriented AmI Systems
- 7.2 Performance Assessment in Real-Time Environments
- 7.3 User Experience and Satisfaction Metrics
- 7.4 Case Studies and Use Cases for Evaluation
- 7.4.1 Smart Homes and Personal Assistance
- 7.4.2 Healthcare Environments and Elderly Care
- 7.4.3 Smart Offices and Workspaces
- 7.5 Results and Insights from Evaluation
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Challenges in Online Management of AmI Systems
- 8.1 Scalability of Real-Time Goal Management
- 8.2 Ensuring Privacy and Security of User Data
- 8.3 Managing Complex Interactions in Multi-User Environments
- 8.4 Resource Constraints in Ambient Intelligence Systems
- 8.5 Handling Uncertainty and Ambiguity in User Goals
- 8.6 Balancing User Autonomy and System Control
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Future Directions and Research Opportunities
- 9.1 Advances in Real-Time Data Processing and AI for AmI
- 9.2 Multi-Agent Systems for Collaborative Goal Management
- 9.3 Integration with Augmented Reality (AR) and Virtual Reality (VR)
- 9.4 User-Centric Ethical and Social Implications
- 9.5 Leveraging 5G and Edge Computing for Enhanced AmI Systems
- 9.6 Cross-Domain Applications for Goal-Driven AmI
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Conclusion
- 10.1 Summary of Key Findings
- 10.2 The Impact of Effective Goal Management in AmI Systems
- 10.3 Closing Remarks on Future of Ambient Intelligence
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