Detect Sensor Drift for a Field Inspection Robot Fleet
Overview
What this challenge is about.
You receive 60 days of telemetry from 12 robots, including IMU readings, camera exposure stats, and the inspection-quality scores produced downstream. Define drift signals (rolling-window statistics, change-point detection) for each sensor. Build a detector that flags a robot when a drift signal crosses a calibrated threshold, with a target false-alarm rate of one alert per robot per month. Prototype a dashboard view showing fleet health and per-robot drift over time. Deliver the detector code, threshold-calibration notebook, and a Figma dashboard mock.
The Brief
What you'll do, and what you'll demonstrate.
Detect sensor drift across a 12-robot inspection fleet with a calibrated false-alarm budget and a usable health dashboard.
Earning criteria — what you'll demonstrate
- Design statistical drift signals from raw telemetry
- Calibrate detection thresholds against a stated alert budget
- Design a fleet-health dashboard for non-engineer operators
- Connect anomaly-detection outputs to a usable operator surface
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
AI Product Designer
Designing the human-facing surface on top of a statistical detector — with defended threshold trade-offs — is exactly an AI product designer's job at fleet-ops companies.
This challenge sharpens
- dashboard-design
- anomaly-detection
- sensor-fusion
MLOps Engineer
Fleet-telemetry drift detection and threshold calibration are MLOps-adjacent skills that bridge into model-monitoring work.
This challenge sharpens
- telemetry-analysis
- anomaly-detection
- python
Data Scientist
Change-point detection and calibrated alerting are bread-and-butter applied data-science skills in any operations-heavy industry.
This challenge sharpens
- change-point-detection
- anomaly-detection
- telemetry-analysis