Course 40531B: Microsoft Cloud Workshop: IoT for Business

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 predictive maintenance of city buses, including machine learning for anomaly 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 when a bulb is out. Easily view all of this information through a centralized reporting dashboard provided by Azure Time Series Insights.

Duration: 1 Day | Location : Online

Course Prerequisites:
None

Request A Quote

Virtual Interactive Lecturer-led Teaching (VILT)

Virtual instruction environments are designed to simulate the traditional classroom or learning experience. Instructor-led training is still the number one delivery method of choice because it allows you to interact and discuss the training material, either individually or in a group setting, and you gain access to expert knowledge from certified instructors. This form of guided learning is impactful and produces positive learning outcomes. Day, evening and Saturday classes are offered.

Course Content

Module 1: Whiteboard Design Session – IoT for business

Lessons

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

– See fewer details

Module 2: Hands-on Lab – IoT for business

Lessons

Azure data, storage, and serverless environment setup
Provision additional Azure services
Create bus and traffic light simulated devices, and add alerts and filters
Create IoT Edge device and custom modules
Run a console app to view critical engine alerts from the Service Bus Queue
Create Azure Function App to ingest critical engine alerts and store them in Cosmos DB
View all data in Azure Time Series Insights

– See more details

At course completion

Learning Objectives:

Use Azure IoT Edge to collect vehicle telemetry data, detect anomalies with the help of a local Azure Machine Learning model, and send the summarized data to Azure IoT Hub as needed
Use IoT Hub to manage IoT devices
Use Azure Time Series Insights to store, visualize, and query the large amounts of time series data generated by various IoT devices, as well as conduct root-cause analysis and anomaly detection
Build a customer application on top of Time Series Insights, using its available REST Query APIs
Use Azure Location Based Services to visualize bus location data on a map