Course 40531-G: Microsoft Cloud Workshop: IoT and the Smart City

Microsoft

Course 40531-G: Microsoft Cloud Workshop: IoT and the Smart City

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In this workshop you will use the unique benefits of Internet of Things (IoT) to build a smart city solution to help improve traffic and public transportation in New York City. Use a combination of the power of the cloud, along with IoT Edge devices to provide anomaly detection of city buses, engine anomalies and aggressive driving detection, location broadcasting to update bus route status, and to send traffic information to help inform the timing of traffic lights. Traffic lights will also receive new IoT devices that can help detect maintenance and performance issues, such as voltage irregularities. Easily view all this information through a centralized reporting dashboard provided by Azure Time Series Insights. Use the IoT Remote Monitoring starter solution to manage and simulate IoT devices, set alerts, and view data on a map. Note: As of January 13, 2020 the lab for this course is unavailable.

Audience Profile

This workshop is intended for Cloud Architects and IT professionals who have architectural expertise of infrastructure and solutions design in cloud technologies and want to learn more about Azure and Azure services as described in the “Summary” and “Skills gained” areas. Those attending this workshop should also be experienced in other non-Microsoft cloud technologies, meet the course prerequisites, and want to cross-train on Azure.

Prerequisites

Course outline

Module 1: Whiteboard Design Session - IoT and the Smart City

Module Overview

This module is designed to help you gain a better understanding of implementing architectures that use IoT data in new and innovative ways. You will design an IoT workflow that begins with a local IoT edge device that collects and analyzes data from various sensors that are connected to it, and intelligently aggregates and sends that data to the cloud when anomalies are detected, other non-critical data is uploaded to cloud storage when a viable internet connection is available. Once the data is uploaded, it is sent to a time-series database for rapid analysis alongside other classes of IoT data to spot and act on correlated information in real-time. You will also configure alerts when certain thresholds are exceeded and configure a remote monitoring solution that manages and sends control messages to IoT devices located within the city limits. At the end of this whiteboard design session, you will be better able to design an end-to-end IoT solution that processes and analyzes data both in the field and in the cloud.

Lessons

Review the customer case study
Design a proof of concept solution
Present the solution

Lab Sessions

Not available for this module

Lab Lessons

Lab lessons not available

After completing this module, students will be able to:

Design an end-to-end IoT solution that processes and analyzes data both in the field and in the cloud.

Module 2: Hands-on Lab - IoT and the Smart City

Module Overview

We have removed the IoT and the Smart City lab documents due to technical issues. Please look for an update in the upcoming months.

Lessons

Set up IoT Remote Monitoring solution environment
Provision additional Azure services
Create bus and traffic light simulated devices, and add alerts and filters
Create IoT Edge device and custom modules
Create an Azure Function to add critical engine alerts to the Service Bus Queue
Run a console app to view critical engine alerts from the Service Bus Queue
Create an Azure Function to ingest critical engine alerts and store them in Cosmos DB
View critical engine alerts in the IoT Remote Monitoring web interface
Add a tag to IoT Edge Device Twin
View all data in Azure Time Series Insights

Lab Sessions

Not available for this module

Lab Lessons

Lab lessons not available

After completing this module, students will be able to:

Use IoT Hub to manage IoT devices.
Configure and run the IoT Remote Monitoring starter solution to provision.
Manage and simulate telemetry for IoT devices via IoT Hub SDKs.
Use Azure IoT Edge to collect vehicle telemetry data.
Detect anomalies and send the summarized data to Azure IoT Hub as needed.
Create a custom endpoint in IoT Hub to route critical alerts to a Service Bus Queue.
Create an Azure function that extracts critical alerts from the Service Bus Queue and stores them in Cosmos DB.
Visualize and query the large amounts of time series data generated by various IoT devices and conduct root-cause analysis and anomaly detection.

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