Exam AI-102 topic 1 question 37 discussion

A. Face. The solution link explains: Embed facial recognition into your apps for a seamless and highly secured user experience. No machine-learning expertise is required. Features include face detection that perceives facial features and attributes—such as a face mask, glasses, or face location—in an image, and identification of a person by a match to your private repository or via photo ID.

A is the answer. https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-identity#face-detection-and-analysis Face detection is required as a first step in all the other scenarios. The Detect API detects human faces in an image and returns the rectangle coordinates of their locations. It also returns a unique ID that represents the stored face data. This is used in later operations to identify or verify faces. Optionally, face detection can extract a set of face-related attributes, such as head pose, age, emotion, facial hair, and glasses. These attributes are general predictions, not actual classifications. Some attributes are useful to ensure that your application is getting high-quality face data when users add themselves to a Face service. For example, your application could advise users to take off their sunglasses if they're wearing sunglasses.

Computer Vision is the best choice for your needs: Why: It offers a flexible, cost-effective solution for detecting PPE compliance (masks and safety glasses) using custom-trained models. Its API-driven approach minimizes development effort, and it can be integrated into a system that processes video or image snapshots every 15 minutes. Costs are manageable since you’re only analyzing periodic snapshots rather than continuous video streams.

Yes, Azure Computer Vision can be used to monitor staff compliance with personal protective equipment (PPE) requirements by detecting whether employees are wearing the necessary safety gear, such as helmets and masks, in real-time. This technology helps ensure workplace safety and compliance with safety standards.

For monitoring staff compliance with PPE requirements in your factory, Azure Video Analyzer for Media (formerly Video Indexer) is the most suitable option. This service can identify staff who have removed masks or safety glasses, perform compliance checks every 15 minutes, and minimize both development effort and costs

Video indexer is the correct answer as it has built-in mask detection. https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/intro-to-spatial-analysis-public-preview?tabs=sa#social-distancing-and-face-mask-detection

Face meets the requirements of identifying staff and checking PPE compliance effectively while keeping both development effort and costs low.

To meet the requirements of identifying staff who have removed masks or safety glasses, performing a compliance check every 15 minutes, and minimizing both development effort and costs, you should use: B. Computer Vision Azure Computer Vision can analyze images and videos to detect whether staff are wearing masks and safety glasses. It can be set up to perform checks at regular intervals, meeting the compliance requirement. For more information, you can refer to the official - https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview

"identify" and "check every 15 minutes" https://learn.microsoft.com/en-gb/azure/ai-services/computer-vision/overview-identity Verify user identity: Verify a person against a trusted face image. This verification could be used to grant access to digital or physical properties such as a bank account, access to a building, and so on. In most cases, the trusted face image could come from a government-issued ID such as a passport or driver’s license, or it could come from an enrollment photo taken in person. During verification, liveness detection can play a critical role in verifying that the image comes from a real person, not a printed photo or mask The goal of liveness detection is to ensure that the system is interacting with a physically present live person at the time of authentication I would say A

The Face API does indeed detect human faces and can return various attributes, which is essential for applications where face recognition or verification is needed. However, in the specific context of monitoring PPE compliance, while face detection is a crucial step, it might not be the most cost-effective and efficient choice compared to using the Computer Vision API directly, especially if the primary task is identifying PPE like masks and safety glasses. The Computer Vision API can perform both object detection (including PPE) and OCR, which might streamline the process with minimal development effort and cost.

Because you have to IDENTIFY staff, it is definitely Face.

"A" makes sense. The task is to recognize people, that DO NOT wear their equipment, not to see who is wearing. Why check for social distancing, identifying masks, goggles, etc. if we only need to find the people that are not wearing that stuff and therefore are easily detected by Face.

Copilot: B To build a monitoring solution for staff compliance with PPE requirements, you should use B. Computer Vision. This service can analyze images and videos to detect whether staff are wearing masks or safety glasses. It is cost-effective and requires minimal development effort compared to other options

C is the right option

The best service to use is B. Computer Vision. Computer Vision can be used to detect and analyze objects in images, including PPE compliance like masks and safety glasses. It meets the requirements for identifying staff who have removed protective equipment, can be run at intervals (e.g., every 15 minutes), and minimizes both development effort and costs compared to more complex solutions like Azure Video Analyzer.

Face is not the best option to identify objects like masks so C Azure Video Analyzer for Media (formerly Video Indexer )

Facial recognition is lower effort than Video Indexer