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I used an IoT sensor and Claude to diagnose a hairdryer

I used an IoT sensor and Claude to diagnose a hairdryer

by lgdimaggio·Mar 2, 2026·2 points·1 comment

AI Analysis

●●●BangerWizardryZero to One

Claude diagnoses machines via real sensor data and ISO-standard fault algorithms, not guessing.

Strengths
  • Grounded diagnostics: frequency spectra and bearing fault detection, not LLM hallucination
  • Bridges hard IoT problem (wideband accelerometry at 26.7 kHz) with Claude via MCP tooling
  • Industrial-grade: uses actual vibration standards and produces actionable maintenance reports
Weaknesses
  • Requires STWIN.box hardware (€2k+), severely limiting accessibility and real-world adoption
  • Proof-of-concept on one device (hairdryer); scalability to diverse industrial equipment unproven
Category
Target Audience

Industrial maintenance teams, IoT developers, predictive maintenance engineers

Similar To

Predictive maintenance platforms (GE Predix, Siemens MindSphere) · Condition monitoring software (Fluke, SKF systems)

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