SteefJan Wiggers Integration MVP Endtoend Io T solution

Steef-Jan Wiggers Integration MVP End-to-end Io. T solution leveraging Microsoft Azure Platform

Steef-Jan Wiggers Microsoft Integration Consultant • • Microsoft Integration MVP Published Author (Inter)national Speaker Tech. Net Wiki Author Blogger Forums Runner 12 th Man Dutch. Workz B. V.

First plug an e. Book § § § http: //www. biztalk 360. com/biztalk-server-extensibility/

Io. T Hype?

Today!

“LEARN ABOUT THE PAST TO PREDICT THE FUTURE”

My experience …. • Wind visualization • Near real time production data • Marketing campaign Wind

Wind Energy production

Io. T Value Chain Biz. Talk Server Wind Turbine Field gateways Cloud gateways (web APIs) WCF Service Web/thick client dashboards

Where do we see Io. T? Mobility Cities Buildings Energy Healthcare Fire safety Light Grid Patient Monitor traffic Pollution Water Solar- and wind energy Traffic reports Flooding Power Gas distribution Monitoring Implants Medical emergency Climate Fuel distribution Tooling Toll roads Drinking water Air quality Power plant Surgical equipment Public transport Lab Waste treatment Lifts and escalators Nuclear waster Taxi Radiology Waste water Sign posts Coal Mines Road network Mobile care Air traffic control Public Order Safety Oil and gas production Diabetes Airports Violations

Io. T Value Chain – Microsoft Azure Web/thick client dashboards Applications Legacy IOT (custom protocols) Devices Cloud gateways (web APIs) Storage adapters IP-capable devices (Windows/Linux) Low-power devices (RTOS) Search and query Stream processing Data analytics (Excel) Field gateways Devices to take action Machine Learning

Azure Io. T Reference Architecture Devices and Data Sources Data Transport Device and Event Processing Provisioning API Presentation Solution Portal IP capable devices Agent Libs Existing Io. T devices Agent Libs Low power devices Identity & Registry Stores Device State Store Cloud Gateway Agent Libs Data Visualization & Presentation Stream Event Processor Storage Control System Worker Role Analytics/ Machine Learning

ECO-System DECISION MAKING ANALYTICS OPERATIONAL UNSTRUCTURED & STRUCTURED DATA Sensors Devices Bots Crawlers ERP CRM LOB APPs

Scenario • Greenhouse • Crop Optimization • Energy efficient

Platform Services Security & Management Cloud Services Service Fabric Hybrid Operations Web Apps API Apps Portal Azure Active Directory Batch Automation Scheduler Mobile Apps Document. DB Logic Apps Redis Cache Azure Search Storage Tables Azure AD Health Monitoring AD Privileged Identity Management Domain Services Storage Queues Biz. Talk Services Hybrid Connections Service Bus Key Vault Store/ Marketplace Data Warehouse Remote. App Azure AD B 2 C Multi-Factor Authentication SQL Database Media Services Content Delivery Network (CDN) API Management Notification Hubs HDInsight Visual Studio Azure SDK VS Online App Insights Backup Analytics & Io. T Data Factory Machine Learning Event Hubs Io. T Hub Stream Analytics Data Lake Data Catalog Mobile Engagement Operational Analytics Import/Export Azure Site Recovery Stor. Simple VM Image Gallery & VM Depot Infrastructure Services

Azure Services for Io. T – Building blocks

Event Hub § §

Event Hubs and Stream Analytics • Cloud-scale telemetry ingestion from websites, apps, and devices • Compatible with more than a million publishers supporting HTTP, AMQP and MQTT • Ingress millions of events per second • SAS based security, with unique token per publisher • Configurable data retention (1 -30 days) • Low latency (<10 ms for volatile data) • Pluggable with other cloud services like Stream Analytics § §

Azure Storage Cloud Storage - Anywhere and anytime access • Blobs, Disks, Tables, Queues and Files Highly Durable, Available and Massively Scalable • Easily build “Internet scale” applications • More than 35 trillion stored objects • 3. 5+ Million requests/sec on average Pay only for what you use Exposed via easy and open REST APIs Rich Client Libraries and Tools

Machine Learning platform in Azure cloud • • • Pre-process data Engineer features Modelling ≣ machine learning ≣ data mining Run R Run Python Experiments (modelling) + Web Services (deployment) • Free • Limited: data size, experiment duration, scalability, speed Paid • Relatively inexpensive, can be free

Power. BI Self-service business intelligence and analytics with Excel and the power of the cloud Q&A

Walkthrough Stream Analytics Field gateway Azure Storage Event Hubs Azure Storage Power BI Analytics (ML, Map Reduce, …)

Event Hubs - Data

Stream Analytics

Data - Wind {"turbinenumber": 1, "poweroutput": 4000, "windspeed": 7, "rotor speed": 7. 5613199116482033, "generatorspeed": 0, "voltage": 0, " current": 0, "reactivepower": 1, "frequency": 11. 56131991164820 3, "powerfactor": 10, "generatortemp": 91. 7747483434038, "nace lletemp": 0, "outsidetemp": 36. 70989933736152, "vibration": 1, "p itch": 0, "brakeactivated": 0, "yawactivated": 0, "Event. Processed. Ut c. Time": "2016 -0505 T 09: 38: 31. 9965947 Z", "Partition. Id": 1, "Event. Enqueued. Utc. Tim e": "2016 -05 -05 T 09: 38: 30. 0990000 Z"} {"turbinenumber": 3, "poweroutput": 4000, "windspeed": 7, "rotor speed": 4. 5253113436164849, "generatorspeed": 0, "voltage": 0, " current": 0, "reactivepower": 1, "frequency": 8. 525311343616484 9, "powerfactor": 10, "generatortemp": 34. 849587692809095, "n acelletemp": 0, "outsidetemp": 13. 939835077123639, "vibration" : 1, "pitch": 0, "brakeactivated": 0, "yawactivated": 0, "Event. Process ed. Utc. Time": "2016 -0505 T 09: 38: 32. 7622059 Z", "Partition. Id": 3, "Event. Enqueued. Utc. Tim e": "2016 -05 -05 T 09: 38: 30. 7790000 Z"}

Stream Analytics

Data - Greenhouse {“greenhouse": 1, "outsidetemp": 36. 70989933736152, “humidity": 90, "E vent. Processed. Utc. Time": "2016 -0505 T 09: 38: 31. 9965947 Z", "Partition. Id": 1, "Event. Enqueued. Utc. Time": "201 6 -05 -05 T 09: 38: 30. 0990000 Z"}

Power BI

Microsoft Pre-configured solution Devices Azure Io. T SDK (OSS) Linux, RTOS, m. Bed, Windows, Android, i. OS Web App Document. DB Storage Blobs Io. T Hub Stream Analytics Event Hub Web Jobs Business Process Logic Apps Azure Active Directory ERP/CRM

Custom vs Automation

Io. T, Azure, Exiting • New technology on all fronts • • • Front-End Integration BI Embedded Cloud • Challenges in speed and agility • More about data than technology!

Contact • Blog: http: //soa-thoughts. blogspot. nl/ • Twitter: @Steef. Jan • Tech. Net Wiki: User. Page Go see the next two Io. T talks: • Kent : Real World Industrial Io. T • Mikael : Azure Io. T Hub beyond Hello world

Thank You