Whisperloop – model evaluation metrics and edge deployment

Sensor Technology Ltd. develops advanced underwater sensing systems, including towed hydrophone arrays and related signal-processing/analytics used in maritime monitoring. The WhisperLoop project is SensorTech’s initiative to operationalize AI-enabled detection, classification, and localization on compact, low-power edge hardware integrated with thin-line towed arrays. The project addresses key challenges SensorTech faces for deploying a field-ready capability: (1) establishing a robust, metric-driven evaluation approach for quantitative model performance, (2) validating inference on constrained edge platforms suitable for uncrewed/autonomous operations, and (3) reducing dependence on high-bandwidth connectivity by enabling reliable, largely autonomous onboard processing. Through the internship, SensorTech will gain practical tools and evidence to support deployment decisions (accuracy, robustness, compute/power constraints), de-risking product development and accelerating transition to commercial offerings. Anticipated benefits include improved competitiveness for real-time maritime monitoring solutions, reduced operating costs for persistent deployments, and strengthened internal capability in edge AI evaluation and deployment workflows.

Faculty Supervisor:

Christopher Whidden

Student:

Partner:

Sensor Technology

Discipline:

Computer science

Sector:

Manufacturing

University:

Dalhousie University

Program:

Accelerate

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