Q: 34

You have a factory that produces food products. You need to build a monitoring solution for staff compliance with personal protective equipment (PPE) requirements. The solution must meet the following requirements: • identify staff who have removed masks or safety glasses. • Perform a compliance check every 15 minutes. • Minimize development effort. • Minimize costs. Which service should you use?

Options

Correct Answer:

Explanation

The Azure AI Face service is the most appropriate choice because it directly addresses the core requirements with minimal effort. The Face detection API can analyze facial attributes, including the presence of accessories like glasses and occlusion, which indicates if the mouth or eyes are covered (e.g., by a mask). This provides a pre-built, highly specific function for PPE compliance. Using this service for periodic image analysis is cost-effective and requires significantly less development than building a custom solution.

Why Incorrect

B. Computer Vision: The standard Computer Vision service provides general object detection, which is less specialized for identifying items on a person's face. It would be less reliable for this task without custom training, which increases development effort.
C. Azure Video Analyzer for Media (formerly Video indexer): This service is designed for in-depth, asynchronous analysis of entire video and audio files. It is overly complex and not cost-effective for a simple, periodic compliance check that can be performed on single image frames.

References

1. Azure AI Face Documentation, "Face detection and attributes": This document explicitly states that the Face service can detect facial attributes. The occlusion attribute determines if parts of the face are blocked, which is used for mask detection. The accessories attribute can identify items like glasses.

Reference: Microsoft Learn, Concepts - Face detection and attributes, Section: "Attributes".

2. Azure AI Face API v1.0 Reference, "Face - Detect With Stream": The API documentation shows that the returnFaceAttributes parameter can be set to request accessories and occlusion, directly supporting the solution's requirements.

Reference: Microsoft Learn, Face API v1.0 reference - Face - Detect With Stream, Section: "Request parameters", returnFaceAttributes enum values.

3. Azure AI Computer Vision Documentation, "Object detection": This documentation shows that Computer Vision detects a set of common objects. While it might detect "glasses," it is not designed to specifically analyze them in the context of a face, nor does it have a built-in attribute for masks.

Reference: Microsoft Learn, Quickstart: Image Analysis 4.0 client library, Section: "Detect objects".

Microsoft Azure AI-102 Real Exam Questions [2026 Update] Quiz

Premium Access Includes