فهرست مطالب

• Foreword
• Preface
• 1. A Brief Introduction to Edge AI
• Defining Key Terms
• Why Do We Need Edge AI?
• Summary
• 2. Edge AI in the Real World
• Common Use Cases for Edge AI
• Types of Applications
• Building Applications Responsibly
• Summary
• 3. The Hardware of Edge AI
• Sensors, Signals, and Sources of Data
• Processors for Edge AI
• Summary
• 4. Algorithms for Edge AI
• Feature Engineering
• Artificial Intelligence Algorithms
• Summary
• 5. Tools and Expertise
• Building a Team for AI at the Edge
• Tools of the Trade
• Summary
• 6. Understanding and Framing Problems
• The Edge AI Workflow
• Do I Need Edge AI?
• Determining Feasibility
• Summary
• 7. How to Build a Dataset
• What Does a Dataset Look Like?
• The Ideal Dataset
• Datasets and Domain Expertise
• Data, Ethics, and Responsible AI
• Data-Centric Machine Learning
• Estimating Data Requirements
• Getting Your Hands on Data
• Storing and Retrieving Data
• Ensuring Data Quality
• Preparing Data
• Building a Dataset over Time
• Summary
• 8. Designing Edge AI Applications
• Product and Experience Design
• Architectural Design
• Accounting for Choices in Design
• Summary
• 9. Developing Edge AI Applications
• An Iterative Workflow for Edge AI Development
• Summary
• 10. Evaluating, Deploying, and Supporting Edge AI Applications
• Evaluating Edge AI Systems
• Deploying Edge AI Applications
• Supporting Edge AI Applications
• What Comes Next
• 11. Use Case: Wildlife Monitoring
• Problem Exploration
• Solution Exploration
• Goal Setting
• Solution Design
• Dataset Gathering
• DSP and Machine Learning Workflow
• Testing the Model
• Deployment
• Iterate and Feedback Loops
• AI for Good
• Related Works
• 12. Use Case: Food Quality Assurance
• Problem Exploration
• Solution Exploration
• Goal Setting
• Solution Design
• Dataset Gathering
• DSP and Machine Learning Workflow
• Testing the Model
• Deployment
• Iterate and Feedback Loops
• Related Works
• 13. Use Case: Consumer Products
• Problem Exploration
• Goal Setting
• Solution Design
• Dataset Gathering
• DSP and Machine Learning Workflow
• Testing the Model
• Deployment
• Iterate and Feedback Loops
• Related Works
• Index
• About the Authors