To reduce the inconvenience caused in locating free parking slots, the company has decided to use image classification at the edge with custom vision and to determine the availability of parking spots in a row in a parking garage.
Identify the sequence in which the below 3 actions are required to be performed.
1- Create an IoT Edge module to perform the query on the device's custom vision web server.
2- Use custom vision and build an image classifier.
3- Send image classifier results to IoT Hub.
Click on the arrows to vote for the correct answer
A. B. C. D. E.Correct Answer: B.
Option A is INCORRECT because the first step will be to create an image classified using custom vision.
This should be followed by the creation of IoT Edge module to perform the query on the device's custom vision web server.
The last step is sending image classifier results to IoT Hub.
Option B is CORRECT.
This sequence is correct.
Option C is INCORRECT because the first step will be to create an image classified using custom vision.
This should be followed by the creation of IoT Edge module to perform the query on the device's custom vision web server.
The last step is sending image classifier results to IoT Hub.
Option D is INCORRECT because the first step will be to create an image classified using custom vision.
This should be followed by the creation of IoT Edge module to perform the query on the device's custom vision web server.
The last step is sending image classifier results to IoT Hub.
Option E is INCORRECT because the first step will be to create an image classified using custom vision.
This should be followed by the creation of IoT Edge module to perform the query on the device's custom vision web server.
The last step is sending image classifier results to IoT Hub.
Reference:
The correct sequence of actions required to use image classification at the edge with custom vision and to determine the availability of parking spots in a row in a parking garage is:
B. 2 -> 1 -> 3
Explanation:
Use custom vision and build an image classifier: The first step is to use custom vision to build an image classifier that can determine whether a parking spot is free or occupied. To do this, images of parking spots need to be gathered, labeled, and then used to train the image classifier. Once the image classifier is trained, it can be deployed to the IoT edge device.
Create an IoT Edge module to perform the query on the device's custom vision web server: The next step is to create an IoT Edge module that can perform queries on the custom vision web server hosted on the device. This module will take images from the camera located at the edge, pass them to the custom vision web server, and then receive the results of the image classification. The module will then determine whether a parking spot is free or occupied and send that information to the IoT Hub.
Send image classifier results to IoT Hub: Finally, the results of the image classification need to be sent to the IoT Hub. This can be done by sending the information from the IoT Edge module to the IoT Hub, which can then be used by the parking garage management system to display the availability of parking spots to drivers.
In summary, the correct sequence of actions is to first build the image classifier using custom vision, then create an IoT Edge module to perform queries on the custom vision web server, and finally send the results of the image classification to the IoT Hub. Therefore, option B, 2 -> 1 -> 3, is the correct sequence of actions.