AI Software Development Kit Monitoring Extension - AI Software Development Kit

Portfolio: IndustrialAI
Product: AI Software Development Kit
Software version: 2.0.0
Language: en-US

Introduction
Overview of Siemens Industrial Edge
Overview of Industrial AI@Edge
AI Software Development Kit Monitoring Extension functionalities
Information about the software license
Safety notes
Cybersecurity information
Cybersecurity information
Note on use
Note regarding the general data protection regulation
Installing AI Software Development Kit Monitoring Extension
Install and run
Using AI Software Development Kit Monitoring Extension
Preparing package and dataset for monitoring
Configuring monitoring function
Deploy the packaged inference pipeline for AI@Edge
Guideline for configuring monitoring function for tabular data
Overview
Prerequisites
Importing pipeline
Configuring tabular reference data
Configure data quality metrics
Configuring data quality metrics overview
Configuring data quality metrics with standard inputs
Configure data quality metrics with different threshold algorithm
Configuring data quality metrics with customized inputs
case 1
Case 2
Case 3
Case 4
Case 5
Case 6
Case 7
Configuring reference data for customized inputs
Configuring alert
Configuring model drift metrics
Configure model drift metrics overview
Configure model drift metrics according to model output category
Configure model drift metrics with standard inputs
Configure model drift metrics with customized inputs
Configuring customized metrics
Create customized metrics script
Configure customized metrics dictionary
Regenerating Edge Configuration Package
Guideline for configuring monitoring function for vision cases
Overview
Prerequisites
Importing pipeline
Configuring vision reference data
Configure data quality metrics
Configuring data quality metrics overview
Configuring camera setting
Configuring databus connection
Configuring data quality metrics with analysis results
Configuring data quality metrics with re-analyzed results
Configuring data quality metrics with updated rules
Configuring alert for data quality
Configuring customized metrics
Adding data quality metrics into pipelines
Configure model drift metrics
Overview
Initialize model drift
Configuring algorithms for model drift
Configuring customized metrics
Adding model drift and customized metrics into pipelines
Regenerating Edge configuration package
View metrics on AI Model Monitor
Overview
View metrics for tabular data cases
View metrics on AI Model Monitor
Metrics for vision data cases
Visualize monitoring result on Edge | level with Flow Creator
Overview
Using Flow Creator template

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