【IoT】 セッション5 『IoT に適したデータ分析』 ------------------ すべてのモノがクラウドの恩恵を受けることが出来る IoT システムを実現するにあたって直面する、レイテンシ、コスト、オフライン対応やセキュリティといった課題を解決するため、エッジコンピューティングが活用されています。このセッションでは、主に AWS Greengrass を用いて、どのようにエッジコンピューティングが実現出来るかを説明します。また、特にエッジコンピューティングと関連の深い、製造現場でどのように活用されているかについてご紹介します。

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Senior Solutions Architect
Toshiaki Enami

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自己紹介
• 名前
• 榎並 利晃（えなみ としあき）
• toshiake@amazon.co.jp
• 役割
• IoT/AI Solution Builder 部長 / シニアソリューションアーキテクト
• 好きなAWSのサービス
• AWS IoT Family
• Amazon Kinesis Family

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Channels DatasetsPipelines Data Stores Jupyter
Notebooks
& Templates

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Amazon Kinesis
Amazon S3

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Datasets

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Jupyter
Notebooks
Predictive
Maintenance
Anomaly
Detection
Forecasting

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ユースケース

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生産状況の見える化を実現するアーキテクチャ例
SNS
Greengrass
IoT Rule (all data)
MES/SCADA
Email
SMS
Factory Machines
Protocol
conversion
AWS IoT/Greengrass/
Device Management/
Device Defender
Amazon QuickSight
AWS IoT Analytics
IoTRule(alerts)
CloudWatch
Cognito
CloudTrail
config
IoT Cert
IAM
Jupyter Notebook
Anomalies

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予兆保全を実現するアーキテクチャ例
Greengrass
IoT Rule (all data)
MES/SCADA
Email
SMS
Factory Machines
Protocol
conversion
ML
Inference
AWS IoT/Greengrass/
Device Management/
Device Defender
Sage MakerML Models
Amazon QuickSight
AWS IoT Analytics
IoTRule(alerts)
CloudWatch
Cognito
CloudTrail
config
IoT Cert
IAM
Jupyter Notebook
Anomalies
SNS

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品質予測, 画像解析を実現するアーキテクチャ例
Greengrass
IoT Rule (all data)
MES/SCADA
Protocol
conversion
Email
SMS
Factory Machines
Vision
Protocol
conversion
ML
Inference
AWS IoT/Greengrass/
Device Management/
Device Defender
ML Models
Amazon QuickSight
AWS IoT Analytics
IoTRule(alerts)
CloudWatch
Cognito
CloudTrail
config
IoT Cert
IAM
Jupyter Notebook
Vision system
images
Sage Master/
Jupyter Notebook
Anomalies
SNS

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デモ

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Get Started
https://docs.aws.amazon.com/iotanalytics/latest/use
rguide/getting-started.html

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まとめ

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