AI-102 Implement computer vision solutions Practice Question
You are designing a computer vision solution for a retail chain to detect shelf stockouts using store camera feeds. Videos are processed in near real-time. Which combination of Azure services should you use to minimize latency and cost?
⚠ Common exam trap
A common mix-up: candidates assume cloud-based video analysis (e.g., Video Indexer or Custom Vision) is always the best choice, overlooking the critical need for edge processing to achieve near real-time latency and cost efficiency in distributed retail environments.
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
✓
Use Azure Video Analyzer for Media (formerly Video Indexer) with an Azure IoT Edge module processing video at the edge.
Azure Video Analyzer for Media (formerly Video Indexer) with an Azure IoT Edge module enables near real-time processing at the edge, minimizing latency by avoiding round trips to the cloud, and reduces cost by processing video locally and only sending relevant insights (e.g., stockout detections) to the cloud. This architecture is ideal for retail chains with store camera feeds that require low-latency, cost-effective stockout detection.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure Video Indexer to analyze videos and send results to Azure SQL Database.
Why it's wrong here
Streaming full video to cloud increases latency.
- ✗
Use Azure Custom Vision to detect stockouts in video frames.
Why it's wrong here
Custom Vision processes single images, not video streams.
- ✗
Use Azure Media Services to transcode video and then run Custom Vision on key frames.
Why it's wrong here
Media Services does not perform AI analysis.
- ✓
Use Azure Video Analyzer for Media (formerly Video Indexer) with an Azure IoT Edge module processing video at the edge.
Why this is correct
Edge processing reduces latency and bandwidth.
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