Exam AI-100 topic 4 question 31 discussion

Actual exam question from Microsoft's AI-100

Question #: 31
Topic #: 4

You have Azure IoT Edge devices that generate measurement data from temperature sensors. The data changes very slowly.
You need to analyze the data in a temporal two-minute window. If the temperature rises five degrees above a limit, an alert must be raised. The solution must minimize the development of custom code.
What should you use?

A. A Machine Learning model as a web service
B. an Azure Machine Learning model as an IoT Edge module
C. Azure Stream Analytics as an IoT Edge module
D. Azure Functions as an IoT Edge module

Show Suggested Answer

Suggested Answer: C 🗳️
References:
https://docs.microsoft.com/en-us/azure/iot-edge/tutorial-deploy-stream-analytics

by sayak17 at Oct. 23, 2020, 1:03 p.m.

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MoustafaB

Highly Voted 4 years, 8 months ago

I guess that stream analytics is correct as the question specifies that we want to minimize custom code

upvoted 9 times

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rveney

Most Recent 2 years ago

You should use Azure Stream Analytics as an IoT Edge module to analyze the data in a temporal two-minute window and raise an alert if the temperature rises five degrees above a limit. Azure Stream Analytics is a fully managed, real-time data analysis service that can process millions of events per second. It can be used to analyze data from IoT devices and other sources, and it supports temporal windowing, filtering, aggregation, and other operations that can be used to detect patterns and raise alerts. You can deploy Azure Stream Analytics as an IoT Edge module to analyze data on the edge and reduce latency and bandwidth costs. You can use the Stream Analytics Query Language (SAQL) to write queries that analyze the data and generate alerts when necessary. You can also use the Azure IoT Hub to manage and monitor your IoT Edge devices and module

upvoted 1 times

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renuka1234

4 years, 4 months ago

IoT Hub is a managed service, hosted in the cloud, that acts as a central message hub for bi-directional communication between your IoT application and the devices it manages. You can use Azure IoT Hub to build IoT solutions with reliable and secure communications between millions of IoT devices and a cloud-hosted solution backend. You can connect virtually any device to IoT Hub. IoT Hub supports communications both from the device to the cloud and from the cloud to the device. IoT Hub supports multiple messaging patterns such as device-to-cloud telemetry, file upload from devices, and request-reply methods to control your devices from the cloud. IoT Hub monitoring helps you maintain the health of your solution by tracking events such as device creation, device failures, and device connections.

upvoted 1 times

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Cornholioz

4 years, 4 months ago

ASA with a Windowing Function

upvoted 1 times

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San_S

4 years, 5 months ago

https://docs.microsoft.com/en-us/azure/iot-edge/tutorial-deploy-stream-analytics

upvoted 1 times

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sayak17

4 years, 8 months ago

it is said that the data changes very slowly. also there is a 2 minute window instead of the 30 seconds shown in the link. could the answer be B ?

upvoted 1 times

uhmdiddlebum

4 years, 8 months ago

An ML model makes implications or predictions across some dataset, but here we just want monitoring or raising an alert, so I think Azure Stream Analytics makes sense. The temperature monitoring use case is also given as an example in the link provided.

upvoted 6 times

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