Real-world deployment
Research gap analysis derived from 2 engineering papers in our local library.
The gap
There is a need to evaluate the performance, scalability, and robustness of AI-driven systems in real-world production settings across various environments.
Consensus across the literature
The papers collectively establish that current research lacks real-world deployment experiences but leave open how these systems perform under practical conditions.
Research trend
Emerging — attention growing, methods still coalescing.
Supporting evidence — 2 representative gaps
- EventVenue: A Comprehensive Full-Stack Web Platform for Intelligent Event Venue Discovery, Booking, and Management (2026) · doi
Performance evaluation was conducted only on a development environment; real-world deployment performance under varied infrastructure conditions is not evaluated.
Keywords: performance evaluation conducted development environment real world deployment varied infrastructure conditions evaluated - Quorum Seal: Cross-Sensor Challenge and Response Attestation for Compromise Detection with Adaptive Multi-Surface Verification (2026) · doi
The prototype was validated only in a local environment; deployment and evaluation in real-world production settings with actual users and threat scenarios is needed.
Keywords: prototype validated local environment deployment evaluation real world production settings actual users threat scenarios needed
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