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Public evaluation

simulate_telemetry_stream

The challenge will be evaluated by assessing the functionality and robustness of the deployed AI service in detecting various simulated quantum network anomalies and providing relevant, actionable recommendations.

Evaluation type
task based
Challenge
AI-Powered Quantum Link Integrity Monitor
Difficulty
Advanced
Rigor
Unspecified

Evaluation overview

How the linked challenge is judged: tasks, benchmarks, and criteria count.

Tasks
2
Benchmarks
0
Criteria
0

Task templates

Inputs and expected outputs.

Task 1

simulate_telemetry_stream

Generates a stream of simulated quantum network telemetry data.

Input format

{ "anomaly_type": "noise", "duration_seconds": 300, "noise_level": 0.1 }

Output format

Stream of JSON objects to a specified Kafka topic.

Task 2

query_anomaly_detection_service

Sends a query to the deployed BentoML service for anomaly detection status and recommendations.

Input format

{ "start_time": "2024-01-01T10:00:00Z", "end_time": "2024-01-01T10:05:00Z" }

Output format

{ "anomalies_detected": true, "anomaly_details": [...], "recommendations": "..." }