Outline for AITRIOS

Level 1	Level 2	Level 3	Level 4	Level 5	Reference
Quick Start	1. Welcome to AITRIOS
	2. Development Workflow Overview
	3. Account Setup and Management
	4. System Introduction
	5. Device Setup	5.1. Device Setup Guide
			5.1.1. Introduction		Device Setup Guide - 1. About this manual
			5.1.2. Preparation Phase		Device Setup Guide - 2. Preparing equipment
				5.1.2.1. Pre-usage Checklist	Device Setup Guide - 2.1. Before using AITRIOS
				5.1.2.2. Hardware Setup	Device Setup Guide - 2.2. Edge Device installation equipment
				5.1.2.3. Console Access	Device Setup Guide - 2.3. Purchasing and launching Console
			5.1.3. Device Registration		Device Setup Guide - 3. Connecting to Console
				5.1.3.1. QR Code Generation	Device Setup Guide - 3.1. Generate enrollment QR code
				5.1.3.2. Device Enrollment	Device Setup Guide - 3.2. Scan QR code
				5.1.3.3. Connection Verification	Device Setup Guide - 3.3. Confirm connection
				5.1.3.4. Device Renaming	Device Setup Guide - 3.4. Rename Edge Device
			5.1.4. Firmware Management		Device Setup Guide - 4. Updating firmware
				5.1.4.1. Firmware Acquisition	Device Setup Guide - 4.1. Obtain firmware
				5.1.4.2. Console Integration	Device Setup Guide - 4.2. Importing firmware
				5.1.4.3. Deployment Configuration	Device Setup Guide - 4.3. Register deployment config
				5.1.4.4. Firmware Deployment	Device Setup Guide - 4.4. Perform deployment
			5.1.5. Device Maintenance		Device Setup Guide - 5. Network/Registration changes
				5.1.5.1. Network Configuration	Device Setup Guide - 5.1. Changing network settings
				5.1.5.2. Device Management	Device Setup Guide - 5.2. Registration changes/deletion
			5.1.6. Appendices		Device Setup Guide - Appendices
				5.1.6.1. Certificate Registration	Device Setup Guide - Appendix A
				5.1.6.1.1. Certificate Acquisition	Device Setup Guide - A.1
				5.1.6.1.2. Device Registration	Device Setup Guide - A.2
				5.1.6.1.3. Service QR Connection	Device Setup Guide - A.3
				5.1.6.2. API Token Management	Device Setup Guide - Appendix B
				5.1.6.3. Adjustment Tools	Device Setup Guide - Appendix C
				5.1.6.4. Factory Reset Recovery	Device Setup Guide - Appendix D
	6. CSV26 Setup	6.1. CSV26 Installation Guide
			6.1.1. Preparation & Requirements		CSV26 Installation Guide - 1. Required Equipment
				6.1.1.1. Essential equipment	CSV26 Installation Guide - 1.1. Essential equipment
				6.1.1.2. Optional equipment	CSV26 Installation Guide - 1.2. Other equipment
			6.1.2. Physical Configuration		CSV26 Installation Guide - 2. QR code and indicator types and positions
				6.1.2.1. QR Code Setup	CSV26 Installation Guide - 2.1. QR code types and positions
				6.1.2.2. Status Indicators	CSV26 Installation Guide - 2.2. Indicator types and positions
			6.1.3. Operational Guidelines		CSV26 Installation Guide - 3. Precautions when using the device
				6.1.3.1. Safety Precautions	CSV26 Installation Guide - 3.1. Safety precautions
			6.1.4. Technical Reference		CSV26 Installation Guide - Appendices
				6.1.4.1. Indicator Patterns	CSV26 Installation Guide - Appendix A: Lighting sequence
				6.1.4.2. Device Specifications	CSV26 Installation Guide - Appendix B: Specification
	7. AIH-IVRW2 Setup	7.1. AIH-IVRW2 Installation Guide
			7.1.1. Preparation & Requirements		AIH-IVRW2 Installation Guide - 1. Required Equipment
				7.1.1.1. Essential equipment	AIH-IVRW2 Installation Guide - 1.1. Essential equipment
				7.1.1.2. Optional equipment	AIH-IVRW2 Installation Guide - 1.2. Other equipment
			7.1.2. Physical Configuration		AIH-IVRW2 Installation Guide - 2. QR code and indicator types and positions
				7.1.2.1. QR Code Setup	AIH-IVRW2 Installation Guide - 2.1. QR code types and placement positions
				7.1.2.2. Status Indicators	AIH-IVRW2 Installation Guide - 2.2. Indicator types and positions
			7.1.3. Operational Monitoring		AIH-IVRW2 Installation Guide - 3. Indicator status display
			7.1.4. Usage Guidelines		AIH-IVRW2 Installation Guide - 4. Precautions when using the device
				7.1.4.1. Wireless LAN Troubleshooting	AIH-IVRW2 Installation Guide - 4.1. When unable to connect
				7.1.4.2. Periodic Operation	AIH-IVRW2 Installation Guide - 4.2. Use of periodic operation
				7.1.4.3. General Operations	AIH-IVRW2 Installation Guide - 4.3. Other operations
			7.1.5. Technical Reference		AIH-IVRW2 Installation Guide - Appendices
				7.1.5.1. Enrollment Sequence	AIH-IVRW2 Installation Guide - Appendix A: Indicator lighting sequence
				7.1.5.2. Device Specifications	AIH-IVRW2 Installation Guide - Appendix B: Specification
	8. SENSAiZ SZP123S-001 setup	8.1. SENSAiZ SZP123S-001 Installation Guide
			8.1.1. Preparation & Requirements		SENSAiZ installation guide - 1. Required Equipment
				8.1.1.1. Essential equipment	SENSAiZ installation guide - 1.1. Essential equipment
				8.1.1.2. Optional equipment	SENSAiZ installation guide - 1.2. Other equipment
			8.1.2. Physical Configuration		SENSAiZ installation guide - 2. QR code and indicator types and positions
				8.1.2.1. QR Code Setup	SENSAiZ installation guide - 2.1. QR code types and positions
				8.1.2.2. Status Indicators	SENSAiZ installation guide - 2.2. Indicator types and positions
			8.1.3. Connection Procedures		SENSAiZ installation guide - 3. LAN cable connection and power On/Off
			8.1.4. Usage Guidelines		SENSAiZ installation guide - 4. Precautions when using the device
			8.1.5. Technical Reference		SENSAiZ installation guide - Appendices
				8.1.5.1. Enrollment Sequence	SENSAiZ installation guide - Appendix A: Indicator lighting sequence
				8.1.5.2. Device Specifications	SENSAiZ installation guide - Appendix B: Specification
	9. Console Operations Guide	9.1. Introduction			Console Manual - 1
			9.1.1. Document Overview		Console Manual - 1.1
			9.1.2. Environment Requirements		Console Manual - 1.2
		9.2. Interface Fundamentals			Console Manual - 2
			9.2.1. UI Capabilities		Console Manual - 2.1
			9.2.2. Screen Layout		Console Manual - 2.2
		9.3. Core Operations
			9.3.1. Authentication		Console Manual - 3.1
				9.3.1.1. Sign In	Console Manual - 3.1
				9.3.1.2. Tenant Switching	Console Manual - 3.10
				9.3.1.3. Sign Out	Console Manual - 3.11
			9.3.2. Device Lifecycle
				9.3.2.1. Enrollment	Console Manual - 3.2
				9.3.2.1.1. Basic Enrollment	Console Manual - 3.2.1
				9.3.2.1.2. QR Enrollment	Console Manual - 3.2.2
				9.3.2.1.3. Certificate Enrollment	Console Manual - 3.2.3
				9.3.2.1.4. Device Renaming	Console Manual - 3.2.4
				9.3.2.1.5. Unenrollment	Console Manual - 3.2.5
				9.3.2.2. Management	Console Manual - 3.3
				9.3.2.2.1. Status Monitoring	Console Manual - 3.3.1
				9.3.2.2.2. Live Preview	Console Manual - 3.3.2
				9.3.2.2.3. Log Inspection	Console Manual - 3.3.3
				9.3.2.2.4. Parameter Application	Console Manual - 3.3.4
				9.3.2.2.5. Model Management	Console Manual - 3.3.5
				9.3.2.2.6. Device Controls	Console Manual - 3.3.6
				9.3.2.2.6.1. Start Inference	Console Manual - 3.3.6.1
				9.3.2.2.6.2. Reboot	Console Manual - 3.3.6.2
				9.3.2.2.6.3. Reset	Console Manual - 3.3.6.3
				9.3.2.2.7. Security Settings	Console Manual - 3.3.7
				9.3.2.2.8. Periodic Mode	Console Manual - 3.3.8
				9.3.2.2.9. Service QR	Console Manual - 3.3.9
				9.3.2.2.10. Device Groups	Console Manual - 3.3.10-11
		9.4. Deployment Operations			Console Manual - 3.4
			9.4.1. AI Model Deployment
				9.4.1.1. Configuration Setup	Console Manual - 3.4.1.1
				9.4.1.2. Deployment Execution	Console Manual - 3.4.1.2
				9.4.1.3. Configuration Removal	Console Manual - 3.4.1.3
			9.4.2. Application Deployment		Console Manual - 3.4.2
			9.4.3. History Tracking		Console Manual - 3.4.3
		9.5. System Configuration			Console Manual - 3.9
			9.5.1. Inference Scheduling		Console Manual - 3.9.1
			9.5.2. Parameter Management		Console Manual - 3.9.2
			9.5.3. Firmware Control		Console Manual - 3.9.3
			9.5.4. Application Administration		Console Manual - 3.9.4
	10. Initial Configuration
		10.1. Network Settings
		10.2. Security Protocols
		10.3. Initialization
	11. First Inference Run
		11.1. Model Selection & Deployment
			11.1.1. Use AITRIOS	Console for AI Model Development
				11.1.1.1. Introduction	Getting Started - 2.1
				11.1.1.2. Edge Device Registration	Getting Started - 2.2
				11.1.1.3. Connecting via QR Code	Getting Started - 2.2.2
				11.1.1.4. Device Preview	Getting Started - 2.2.3
				11.1.1.5. AI Model Development	Getting Started - 2.3
				11.1.1.5.1. Project Creation	Getting Started - 2.3.2
				11.1.1.5.2. Dataset Import	Getting Started - 2.3.3
				11.1.1.5.3. Model Training	Getting Started - 2.3.5
				11.1.1.6. AI Model Deployment	Getting Started - 2.5.3
		11.2. Running Inference
			11.2.1. Starting Inference		Getting Started - 2.6.3
			11.2.2. Result Interpretation
			11.2.3. Confirm Results		Getting Started - 2.7.2
			11.2.4. Use Cloud SDK to Visualize Data		Getting Started - 3.5
				11.2.4.1. Retrieve Device List	Getting Started - 3.5.3
				11.2.4.2. Display Images	Getting Started - 3.5.5
				11.2.4.3. Superimpose Inference Results	Getting Started - 3.5.8
	12. Next Steps
		12.1. Learning Path
		12.2. Support Contacts
Development Guides	1. SDK Getting Started
		1.1. Introduction to the SDK			SDK Getting Started - 1
		1.2. Environment Setup			SDK Getting Started - 2
			1.2.1. Prerequisites		SDK Getting Started - 2.1
			1.2.2. Installation Steps		SDK Getting Started - 2.2
		1.3. Basic Usage			SDK Getting Started - 3
			1.3.1. Initializing the SDK		SDK Getting Started - 3.1
			1.3.2. Core Functions		SDK Getting Started - 3.2
		1.4. Troubleshooting			SDK Getting Started - 4
			1.4.1. Common Issues		SDK Getting Started - 4.1
			1.4.2. Debugging Tips		SDK Getting Started - 4.2
	2. Edge Application Implementation Guide				Edge Application Implementation Guide
		2.1. About Edge Application			Edge Application Implementation Guide - 2
			2.1.1. Edge Application Overview		Edge Application Implementation Guide - 2.1
			2.1.2. Basic Sequence of Edge Applications		Edge Application Implementation Guide - 2.2
		2.2. Creating and Training the AI Model			Edge Application Implementation Guide - 3
			2.2.1. Preparing Training Images		Edge Application Implementation Guide - 3.1
			2.2.2. Training the AI Model		Edge Application Implementation Guide - 3.2
			2.2.3. Quantization of AI Model		Edge Application Implementation Guide - 3.3
			2.2.4. Deploying the AI Model		Edge Application Implementation Guide - 3.4
		2.3. Creating and Deploying the Edge Application			Edge Application Implementation Guide - 4
			2.3.1. Overview of Edge Application to Create		Edge Application Implementation Guide - 4.1
			2.3.2. Changes to FlatBuffers Schema and Creation of C++ Header		Edge Application Implementation Guide - 4.2
			2.3.3. Changing the Initialization Process		Edge Application Implementation Guide - 4.3
			2.3.4. Changing Analysis Process		Edge Application Implementation Guide - 4.4
			2.3.5. Building and Debugging		Edge Application Implementation Guide - 4.5
			2.3.6. Deploying Edge Application to an Edge Device		Edge Application Implementation Guide - 4.6
		2.4. Inference Execution on an Edge Device			Edge Application Implementation Guide - 5
			2.4.1. Editing Command Parameter		Edge Application Implementation Guide - 5.1
			2.4.2. Command Parameter Registration and Binding to Edge Devices		Edge Application Implementation Guide - 5.2
			2.4.3. Performing Inferences		Edge Application Implementation Guide - 5.3
		2.5. Getting and Deserializing Inference Result Metadata			Edge Application Implementation Guide - 6
			2.5.1. Generating Source Code for Deserialization		Edge Application Implementation Guide - 6.1
			2.5.2. Retrieving and Deserializing Inference Result Metadata from Console		Edge Application Implementation Guide - 6.2
		2.6. Checking the Output Tensor Array in an Edge Application Implementation			Edge Application Implementation Guide - 7
			2.6.1. About DNN Params		Edge Application Implementation Guide - 7.1
			2.6.2. How to Get DNN Params		Edge Application Implementation Guide - 7.2
			2.6.3. Sample Code for Getting DNN Params		Edge Application Implementation Guide - 7.3
			2.6.4. Edge Application Implementation Notice		Edge Application Implementation Guide - 7.4
		2.7. Appendices
			2.7.1. Change Code for Creating Edge Application		Edge Application Implementation Guide - Appendix A
			2.7.2. Image Creation Script Example		Edge Application Implementation Guide - Appendix B
	3. Model Development Suite				Console Manual - 3.5-3.7
		3.1. Introduction to TFLite Import and Deployment
			3.1.1. Overview of TFLite Workflow		TFLite Guide 1
			3.1.2. Key Components: AI Models, Edge Applications, and Inference Verification		TFLite Guide 1
			3.1.3. Recommended Environment: Codespaces		TFLite Guide 1
			3.1.4. Reference to Inference Operation Guide		TFLite Guide 1
		3.2. Model Creation
			3.2.1. New Model Setup		Console Manual - 3.5.1.1
			3.2.2. Model Retraining		Console Manual - 3.5.1.2
			3.2.3. Model Import		Console Manual - 3.5.2.1
			3.2.4. Model Updates		Console Manual - 3.5.2.2
		3.3. Training Workflows
			3.3.1. Standard Training		Console Manual - 3.6.1
			3.3.2. Edge Data Training		Console Manual - 3.6.2
		3.4. Labeling System			Console Manual - 3.7
			3.4.1. Image Annotation		Console Manual - 3.7.1
			3.4.2. Training Execution		Console Manual - 3.7.2
			3.4.3. Label Management		Console Manual - 3.7.3-5
		3.5. Model Conversion
			3.5.1. TFLite Model Import		TFLite Guide 2.2
			3.5.2. Model Conversion Process		TFLite Guide 2.3
		3.6. Deployment Configuration
			3.6.1. Registration Process		TFLite Guide 2.4
			3.6.2. Deployment Execution		TFLite Guide 2.5
		3.7. Custom Vision AI Model Deployment			Custom Vision Guide
			3.7.1. Creating AI Model with Custom Vision		Custom Vision Guide - 2
				3.7.1.1. Create a Custom Vision Project	Custom Vision Guide - 2.1
				3.7.1.2. Dataset Preparation	Custom Vision Guide - 2.2
				3.7.1.2.1. Preparing Training Images	Custom Vision Guide - 2.2.1
				3.7.1.2.2. Importing Images	Custom Vision Guide - 2.2.2
				3.7.1.2.3. Labeling Images	Custom Vision Guide - 2.2.3
				3.7.1.3. Training and Saving AI Model	Custom Vision Guide - 2.3
				3.7.1.3.1. Training AI Model	Custom Vision Guide - 2.3.1
				3.7.1.3.2. Saving AI Model	Custom Vision Guide - 2.3.2
				3.7.1.4. Converting AI Models in Console	Custom Vision Guide - 2.4
			3.7.2. Deploying AI Model and Edge Application		Custom Vision Guide - 3
				3.7.2.1. Deploy AI Model to Edge Device	Custom Vision Guide - 3.1
				3.7.2.2. Deploy Edge Application	Custom Vision Guide - 3.2
			3.7.3. Setting Command Parameters and Running Inference		Custom Vision Guide - 4
				3.7.3.1. Creating Command Parameters File	Custom Vision Guide - 4.1
				3.7.3.2. Registering Command Parameters	Custom Vision Guide - 4.2
				3.7.3.3. Performing Inference	Custom Vision Guide - 4.3
			3.7.4. Verifying Inference Results		Custom Vision Guide - 5
				3.7.4.1. Getting Inference Result Metadata	Custom Vision Guide - 5.1
				3.7.4.2. Preparing for Deserialization	Custom Vision Guide - 5.2
				3.7.4.3. Deserializing Inference Results	Custom Vision Guide - 5.3
			3.7.5. Technical Appendices		Custom Vision Guide - Appendices A-D
				3.7.5.1. Inference Results Verification with Console REST API	Custom Vision Guide - A.1
				3.7.5.2. Deserialization Techniques	Custom Vision Guide - A.2
				3.7.5.2.1. Python Sample Code	Custom Vision Guide - A.2.1
				3.7.5.2.2. TypeScript Sample Code	Custom Vision Guide - A.2.2
				3.7.5.3. Image Capture for Training	Custom Vision Guide - B
				3.7.5.3.1. Capturing with Edge Device	Custom Vision Guide - B.1
				3.7.5.3.2. Retrieving Captured Images	Custom Vision Guide - B.2
				3.7.5.4. Sample Code for Deserialization and Metadata Retrieval	Custom Vision Guide - C
				3.7.5.5. Custom Vision Specifications	Custom Vision Guide - D
		3.8. Keras Model Deployment			Keras Guide
			3.8.1. Quantization with Model Compression Toolkit		Keras Guide - 4
				3.8.1.1. Overview of Model Compression Toolkit	Keras Guide - 4.1
				3.8.1.2. Quantization Process	Keras Guide - 4.2
			3.8.2. Accuracy Verification		Keras Guide - Appendix A
				3.8.2.1. Comparison of Model Accuracy Before and After Quantization	Keras Guide - A.1
				3.8.2.2. Image Contribution Analysis	Keras Guide - A.2
			3.8.3. Deployment and Inference		Keras Guide - 5
				3.8.3.1. Importing and Converting the AI Model	Keras Guide - 5.1
				3.8.3.2. Deploying the AI Model	Keras Guide - 5.2
				3.8.3.3. Deploying the Edge Application	Keras Guide - 5.3
			3.8.4. Inference Execution and Verification		Keras Guide - 6
				3.8.4.1. Creating Command Parameters File	Keras Guide - 6.1
				3.8.4.2. Registering Command Parameters	Keras Guide - 6.2
				3.8.4.3. Performing Inference	Keras Guide - 6.3
			3.8.5. Inference Result Verification		Keras Guide - 7
				3.8.5.1. Getting Inference Result Metadata	Keras Guide - 7.1
				3.8.5.2. Verifying Inference Results	Keras Guide - 7.2
		3.9. PyTorch Model Deployment			PyTorch Guide
			3.9.1. Quantization with Model Compression Toolkit		PyTorch Guide - 4
				3.9.1.1. Overview of Model Compression Toolkit	PyTorch Guide - 4.1
				3.9.1.2. Quantization Process	PyTorch Guide - 4.2
			3.9.2. Deployment and Inference		PyTorch Guide - 5
				3.9.2.1. Importing and Converting the AI Model	PyTorch Guide - 5.1
				3.9.2.2. Deploying the AI Model	PyTorch Guide - 5.2
				3.9.2.3. Deploying the Edge Application	PyTorch Guide - 5.3
			3.9.3. Inference Execution and Verification		PyTorch Guide - 6
				3.9.3.1. Creating Command Parameters File	PyTorch Guide - 6.1
				3.9.3.2. Registering Command Parameters	PyTorch Guide - 6.2
				3.9.3.3. Performing Inference	PyTorch Guide - 6.3
			3.9.4. Inference Result Verification		PyTorch Guide - 7
				3.9.4.1. Getting Inference Result Metadata	PyTorch Guide - 7.1
				3.9.4.2. Verifying Inference Results	PyTorch Guide - 7.2
	4. Inference Operation Guide
		4.1. Introduction to Inference Operations			Inference Operation Guide - 1
		4.2. Data Flow Overview			Inference Operation Guide - 1.1
		4.3. Steps from Inference Preparation to Execution			Inference Operation Guide - 1.2
		4.4. Specific Inference Operations			Inference Operation Guide - 1.3
		4.5. Creating and Deploying AI Models			Inference Operation Guide - 2
			4.5.1. Using Custom Vision on the Console		Inference Operation Guide - 2.1
			4.5.2. Using Brain Builder		Inference Operation Guide - 2.2
			4.5.3. Creating AI Models using Keras or PyTorch		Inference Operation Guide - 2.3
		4.6. Preparing and Deploying an Edge Application			Inference Operation Guide - 3
			4.6.1. Preparing an Edge Application		Inference Operation Guide - 3.1
			4.6.2. Related Manuals for Edge Application Implementation		Inference Operation Guide - 3.2
			4.6.3. Registering and Deploying an Edge Application		Inference Operation Guide - 3.3
		4.7. Setting Inference Behavior			Inference Operation Guide - 4
			4.7.1. Configuring Normal Operation		Inference Operation Guide - 4.1
			4.7.2. Inference Frame Rate		Inference Operation Guide - 4.2
			4.7.3. Configuring Periodic Operation		Inference Operation Guide - 4.3
		4.8. Executing and Checking Inference			Inference Operation Guide - 5
			4.8.1. Procedure for Executing Inference and Getting Metadata		Inference Operation Guide - 5.1
			4.8.2. About Console Saved Data and Changing the Transfer Destination		Inference Operation Guide - 5.2
		4.9. Switching DNN Overview and Instructions			Inference Operation Guide - 6
			4.9.1. Switching DNN Objectives		Inference Operation Guide - 6.1
			4.9.2. Switching DNN Operation Overview		Inference Operation Guide - 6.2
			4.9.3. Instructions to Inference		Inference Operation Guide - 6.3
	5. Advanced Technical Setup
		5.1. Environment Configuration
			5.1.1. Codespaces/WSL/Docker Setup		Getting Started 3.1-3.4
			5.1.2. Local Linux Environment		Getting Started 3.1-3.4
		5.2. Cloud App Development
			5.2.1. Backend/Frontend Setup		Getting Started 4.1-4.10
			5.2.2. API Implementation		Getting Started 4.1-4.10
				5.2.2.1. getDevices API	Getting Started 4.5
				5.2.2.2. getImageDirectories API	Getting Started 4.7
			5.2.3. Metadata Handling		Getting Started 4.10
	6. Annotation & Training
		6.1. Dataset Annotation			Getting Started 2.3.4
		6.2. Training Analysis			Getting Started 2.3.6
	7. UI Component Library
		7.1. Device Selection UI			Getting Started 4.5
		7.2. Directory Browser			Getting Started 4.7
		7.3. Bounding Box Renderer			Getting Started 4.10
API & SDK References	1. System API Reference
	2. Console REST API Specification				Console REST API Usage Guide
		2.1. About the Console REST API			Console REST API Usage Guide - 1
			2.1.1. Overview of Available Functions
			2.1.2. User Interface vs REST API Capabilities
		2.2. Precautions and Requests for Using REST API			Console REST API Usage Guide - 2
		2.3. Classification of Console REST API			Console REST API Usage Guide - 3
		2.4. Examples of API Call Sequences			Console REST API Usage Guide - 4
			2.4.1. Registering Command Parameter and Binding to Device		Console REST API Usage Guide - 4.1
			2.4.2. Starting and Stopping Inference		Console REST API Usage Guide - 4.2
			2.4.3. Exporting Images		Console REST API Usage Guide - 4.3
			2.4.4. Getting Images and Inference Result Metadata		Console REST API Usage Guide - 4.4
			2.4.5. Monitoring Device Operation		Console REST API Usage Guide - 4.5
			2.4.6. Creating a Custom Vision Project and Uploading Images and Annotations		Console REST API Usage Guide - 4.6
		2.5. Flow of Console REST API Call			Console REST API Usage Guide - 5
			2.5.1. Confirming Endpoints and Obtaining Access Token		Console REST API Usage Guide - 5.1
			2.5.2. Calling Console REST API		Console REST API Usage Guide - 5.2
			2.5.3. Sample Code for Access Token Update (Python)		Console REST API Usage Guide - 5.3
		2.6. Sample Code Appendix			Console REST API Usage Guide - Appendix A
	3. Technical Specifications
		3.1. Parameter Documentation			Console Manual - Appendices A/D/E
		3.2. Error Code Reference			Console Manual - Appendix B
		3.3. Model Requirements			Console Manual - Appendix C
		3.4. Edge Application Implementation Requirements			Edge Application Implementation Requirements
			3.4.1. AI Model Requirements		Edge Application Implementation Requirements - 2
				3.4.1.1. Memory Requirements of AI Model	Edge Application Implementation Requirements - 2.1
				3.4.1.2. Implementation Requirements for AI Models	Edge Application Implementation Requirements - 2.2
			3.4.2. Edge Application Implementation Requirements		Edge Application Implementation Requirements - 3
				3.4.2.1. Application Memory Requirements	Edge Application Implementation Requirements - 3.1
				3.4.2.2. Application Implementation Requirements	Edge Application Implementation Requirements - 3.2
			3.4.3. Memory Requirements for Data Send		Edge Application Implementation Requirements - 4
				3.4.3.1. Memory Requirements for Inference Results Metadata Send	Edge Application Implementation Requirements - 4.1
				3.4.3.2. Size Requirements for Sending Output Tensors	Edge Application Implementation Requirements - 4.2
	4. Functional Specifications
	5. API Usage Guides
		5.1. REST API Call Procedures
		5.2. Authentication Mechanisms
		5.3. Request and Response Formats
		5.4. Error Handling
Sample Applications	1. Car Intrusion Detection
	2. Parking Lot Vacancy Identification
	3. People Counting
	4. Cloud SDK Samples
		4.1. Python
		4.2. TypeScript
		4.3. Visualization
		4.4. Deserialization
Advanced Topics	1. Advanced Analytics
		1.1. Inference Data Analysis			Console Manual - 3.8
	2. Hub Mode Operations				Console Manual - 4
		2.1. Provisioning Hub			Console Manual - 4.1
		2.2. Data Hub			Console Manual - 4.2
	3. Detailed Configuration
		3.1. Firmware Deployment			Getting Started 2.2.4
		3.2. PPL Parameters			Getting Started 2.5.4
		3.3. Model Conversion			Getting Started 2.4
		3.4. Inference Tuning			Getting Started 2.6.2
	4. Custom Model Deployment
	5. External Transfer Settings
		5.1. AWS S3
			5.1.1. Introduction to AWS S3 Transfer
			5.1.2. Prerequisites for AWS S3 Setup
			5.1.3. Operational Environment for AWS S3
			5.1.4. External Transfer Configuration
			5.1.5. AWS S3 Setup
				5.1.5.1. Preparation Before Starting AWS S3
				5.1.5.2. Starting the AWS S3 Transfer
			5.1.6. Checking Operation After Setting External Transfer
				5.1.6.1. Obtaining Inference Results and Images
				5.1.6.2. Checking Obtained Inference Results and Images
			5.1.7. Remarks on AWS S3 Communication
		5.2. Azure Event Hubs
		5.3. HTTP Server
			5.3.1. Introduction to HTTP Server Transfer
			5.3.2. Prerequisites for HTTP Server Setup
			5.3.3. Operational Environment for HTTP Server
			5.3.4. External Transfer Configuration
			5.3.5. HTTP Server Setup
				5.3.5.1. Preparation Before Starting HTTP Server
				5.3.5.2. Starting the HTTP Server
			5.3.6. Checking Operation After Setting External Transfer
				5.3.6.1. Obtaining Inference Results and Images
				5.3.6.2. Checking Obtained Inference Results and Images
			5.3.7. Remarks on HTTP Communication
		5.4. Azure Blob Storage
			5.4.1. Introduction to Azure Blob Storage Transfer
			5.4.2. Prerequisites for Azure Blob Storage Setup
			5.4.3. Operational Environment for Azure Blob Storage
			5.4.4. External Transfer Configuration
			5.4.5. Azure Blob Storage Setup
				5.4.5.1. Preparation Before Starting Azure Blob Storage
				5.4.5.2. Starting the Azure Blob Storage Transfer
			5.4.6. Checking Operation After Setting External Transfer
				5.4.6.1. Obtaining Inference Results and Images
				5.4.6.2. Checking Obtained Inference Results and Images
			5.4.7. Remarks on Azure Blob Storage Communication