AI-102 Implement computer vision solutions Practice Question
You need to analyze a video stream from a security camera to count the number of people entering a building. Which Azure AI service is most suitable?
⚠ Common exam trap
The key trap is that candidates often choose Azure AI Video Indexer (Option D) because it is associated with video analysis, but it is designed for indexing and analyzing video files, not real-time streaming. Azure AI Spatial Analysis (Option A) is the correct choice for live video streams and people counting scenarios.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure AI Spatial Analysis
Azure AI Spatial Analysis is the most suitable service because it is purpose-built for real-time spatial analysis of video streams, including counting people entering a building. It can process live camera feeds and detect when people cross a line or enter a zone, providing real-time counts. In contrast, Azure AI Video Indexer is designed for analyzing recorded video files, not live streams, making it less suitable for real-time security camera analysis. Other options like Custom Vision and Computer Vision are for image classification and image analysis, respectively, not optimized for video streams.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure AI Spatial Analysis
Why this is correct
Azure AI Spatial Analysis ingests live video and applies computer vision operations, including people counting and zone-based entry/exit tracking, directly on the stream. It satisfies the real-time counting constraint that image-only services cannot, since Azure AI Vision handles still images rather than continuous camera feeds.
- ✗
Azure AI Custom Vision
Why it's wrong here
Custom Vision trains image classification and object detection models on still images; it cannot process a live video stream or track people across frames. It is tempting because you could train a person detector, but the scenario needs temporal tracking, which Azure AI Video Indexer supplies natively.
- ✗
Azure AI Computer Vision
Why it's wrong here
Computer Vision handles still images and limited spatial analysis, not continuous multi-object tracking across frames needed to count people crossing a boundary. It is tempting because it offers object detection, but the correct service, Video Indexer, provides person detection and tracking within video streams.
- ✗
Azure AI Video Indexer
Why it's wrong here
Video Indexer extracts insights such as faces, topics and OCR from stored video, but it does not provide real-time people counting on a live camera stream. It is tempting because it processes video, yet the scenario requires live stream analysis, which Azure AI Vision's spatial analysis feature delivers.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.