SOLUTION BRIEF

WISE-DeviceOn for Azure AI + Machine Learning
MLOps for Custom Vision AI Model and Continuous Deployment

We all know that AIoT has become the main trend to solve as
many as production or management problems. Therein, the key
AI models are always customized and frequently adjusted for theproblems to be solved. In addition, it’s going to leverage IoTtechnologies to collect training data automatically and efficiently
so we also need a stable, scalable and securable place to store
those raw data. We also need to consider the tasks for computing
performance and continuous deployment, which means to takecare about how to realize optimized inference and model training.
Challenge
It’s hard for enterprises to leverage AI solutions efficiently because
there are various complicated issues about data collection, AI model,
computing performance and centralized deployment. Even though
they may hire AI-related engineers, specialists and scientists, in the
beginning they still need to take lots of efforts to set up an AI solution
probably just for a POC. In addition, the followed maintenance about
continuous training and AI model deployment will also be criticalissues to be dealt with. It involves many complex techniques to beconsidered and integrated.
Solution
WISE-DeviceOn can leverage certified AI models for object detection
and image classification in Azure Custom Vision to help enterprises
build up their own vision AI solution in an efficient way. Moreover, anoverall lifecycle management from model training to edge AI inferenceis effectively implemented through the integration of DeviceOn andAzure, like the mentioned MLOps.
Edge Inference with Optimized Computing
The adopted inference engine here is ONNX Runtime. Developers
can use the same application development framework to support
accelerated inference on various AI chips through relatedEP(Execution Provider). Within this solution, the inference runtime candirectly support AI models pre-trained and re-trained by Azure Custom
Vision.

© 2021 Advantech Co., Ltd. All rights reserved.

Highlights of Azure Custom Vision
Overall Azure AI + Machine Learning
aims to create the next generation ofapplications using artificial intelligencecapabilities for any developer and any
scenario. Its Cognitive Services offer acomprehensive family of AI services andcognitive APIs to help you buildintelligent apps. Therein Azure Custom
Vision can easily customize your own
state-of-the-art computer vision models
that fit perfectly with your unique usecase. Just bring a few examples oflabeled images through friendly UI and
let Custom Vision do the hard work.
Start training your computer visionmodel by simply uploading and labelinga few images. The model tests itself onthese and continually improves precision
through a feedback loop as you add
images. To speed development, use
customizable, built-in models for retail,manufacturing, and food.
• Customization to your scenario
Set your model to perceive aparticular object for your use case
• Intuitive model creation
Easily build your image identifiermodel using the simple interface• Flexible deployment
Run Custom Vision in the cloud or on
the edge in containers• Built-in security
Rely on enterprise-grade security andprivacy for your data and any trainedmodels

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SOLUTION BRIEF

Project Solution
Data Collection via DeviceOn
WISE-DeviceOn provides a generalized WISE-Agent to run IoT
services at edges and connect to your DeviceOn server. For AI
MLOps, WISE-Agent has additional plug-ins to route periodical
images captured from cameras, videos or other resources. It alsotransmits the AI inference data and results to your loud storage andDeviceOn Server.
Your Own AI Model via Azure Custom Vision
Azure Custom Vision provides pre-trained models about object
detection and classification to train and re-train your own model. Theformer can detect multiple objects and their positions in a single
image. The latter just can tell us if a single image represents aspecific object or condition. When it needs to label massive newimages, Azure Custom Vision has an auto pre-labeling function tohelp users create preliminary labeled data. After finishing datalabeling, it’s able to train/re-train and export a custom AI model foryour specific application.

About Microsoft Azure
Microsoft Azure is an ever-expanding
set of cloud computing services that
help organizations address businesschallenges. With Azure, yourbusiness or organization has the
freedom to build, manage, and deploy
applications on a massive, global
network using your preferred tools
and frameworks.
For more information, visit
www.microsoftazure.com

Continuous Delivery for AI Model via DeviceOn
DeviceOn has not only realized enhanced OTA functions throughthe DeviceOn App store module, but also further leveraged OTA into
MLOps pipelines. Once a custom model is exported by Azure
Custom Vision, Azure Function service integrated in this solution willfurther build a docker image automatically for later edge inference
deployment and then push the image onto the DeviceOn App store.
Enhanced DeviceOn OTA with friendly GUI can efficiently applyversion control on AI model management and continuously delivery
any required AI model(s) to a batch of edges.
Solution Architecture and Data Flow

© 2021 Advantech Co., Ltd. All rights reserved.

2SOLUTION BRIEF

Project Results
Use Case #1: Signage Anomaly Detection via Azure Custom
Vision within Azure Cognitive Services
There are more and more unattended digital signages around ourlives. Some signage anomalies, such as freezed player screen andunexpected pop-up messages, may happen to hinder the playingcontent. However it’s always hard to notify administrators instantly tosave the downtime and unnecessary waste. Therefore this solution
leverages Azure Custom Vision to train a custom AI model for
detecting the three types of anomaly in red marks. Once theabnormal conditions are detected by the AI inference runtime atedge, administrators can be notified immediately through DeviceOn
notification.

About Advantech WISE-DeviceOn
Advantech's IoT software solution,
WISE-DeviceOn, is aimed at IoT
device remote monitoring andmanagement. This IoT Platform
Architecture includes IoT device,system, and cloud layers. Advantech
strives to integrate partner solutions
and enable seamless, secure IoT
solutions from the edge-to-the cloud by
providing pre-integrated, pre-validated
hardware and software building blocks.
For more information, visit:https://select.advantech.com/deviceon/

Advantech Certified Devices
Advantech’s WISE-DeviceOn comes
preloaded with over 600 Advantech
certified board and system models thatdeliver device data and software
management. WISE-DeviceOn
facilitates diverse IoT management byoffering free license support to certifieddevices.
Use Case #2: Production Line Balance for Smart Factory via
Azure Percept to Accelerate Intelligence at the Edge
Line balance is a critical topic in factory to manage productionefficiency, quality and safety. We trained a custom model to detect
workpieces, hats, gloves and so on by Azure Custom Vision, andfurther adopted Azure Percept to realize accelerating edge AI. Once
products or SOPs change over, DeviceOn server can facilitate
MLOps to receive a re-trained model from Azure Custom Vision andthen deploy it to any required Azure Percept efficiently.

© 2021 Advantech Co., Ltd. All rights reserved.

For certified device information, visit:https://www.advantech.com/solutions/e
mbedded-modules-and-design-inservices

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