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Edge-Inference Pipeline for a Smart-Factory Vibration Monitor

FreeVerified credential4 weeksAdvanced

Overview

What this challenge is about.

Edge-Inference Pipeline for a Smart-Factory Vibration Monitor. Advanced challenge in code. Writing production code that solves real engineering problems, ear...

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Run vibration anomaly detection on-device on ESP32-S3 with under 1 percent false-positive weekly and under 1 MB/day MQTT egress per machine.

This is not a coding exercise. It is the work a software engineer does between a Jira ticket and a merged PR. That distinction matters to every hiring manager who has seen candidates solve LeetCode problems and none who have shipped production code under real constraints.

When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."

Earning criteria — what you'll demonstrate

  • Design a multi-stage edge-inference pipeline on constrained MCUs
  • Quantize/distill ML models to fit edge memory + latency budgets
  • Evaluate cyber-physical systems with operationally relevant metrics
  • Specify deployment architectures that respect network + power constraints

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Internet of Things and Cyber-Physical Systems

Master · Embedded And Iot

Strong alignment

This challenge maps to Internet of Things and Cyber-Physical Systems at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.

One more thing

You can put a credential on your CV by Friday.

Edge-Inference Pipeline for a Smart-Factory Vibration Monitor