Sina Bolouri

Project

Portable Predictive Maintenance Assistant

A Raspberry Pi 5 and AI HAT+ based portable predictive maintenance platform combining thermal imaging, vibration analysis, AI-assisted troubleshooting, maintenance knowledge retrieval, and field documentation.

in_progressRaspberry Pi 5Raspberry Pi AI HAT+ 2PythonOpenCVFLIR Lepton 3.5PureThermal Mini ProADXL357LinuxV4L2FFmpegWeb UILLM
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Portable Predictive Maintenance Assistant

A portable industrial maintenance platform built around Raspberry Pi 5 and AI HAT+ 2. The system combines thermal imaging, vibration monitoring, maintenance knowledge retrieval, AI-assisted troubleshooting, and field documentation into a single handheld tool intended for predictive maintenance of motors, bearings, gearboxes, conveyors, and other mechanical assets.

Problem

Industrial maintenance technicians often carry multiple tools for thermal inspections, vibration measurements, troubleshooting, documentation lookup, and note taking. Existing tools can be expensive, disconnected from one another, and often lack onboard intelligence for analysis and recommendations.

Solution

Create a portable edge-AI device that combines:

  • Thermal imaging
  • Vibration analysis
  • Acoustic monitoring
  • Maintenance documentation retrieval
  • AI-powered troubleshooting
  • Meeting and conversation summarization

The device is designed to operate locally using a Raspberry Pi access point without requiring enterprise Wi-Fi access.

User Experience

A technician:

  1. Powers on the device.
  2. Connects directly to the Raspberry Pi access point.
  3. Opens a local dashboard.
  4. Captures thermal scans.
  5. Records vibration measurements.
  6. Receives AI-assisted maintenance insights.
  7. Searches repair instructions and SOPs.
  8. Documents findings and work order notes.

Future versions may include a dedicated mobile application.

Current Status

In active prototype development.

Thermal imaging hardware has been acquired and successfully connected. Initial thermal frame acquisition from the FLIR Lepton 3.5 through the PureThermal Mini Pro has been validated.

Vibration sensing hardware selection has been completed but full integration remains in progress.

Tech Stack

Hardware

  • Raspberry Pi 5
  • Raspberry Pi AI HAT+ 2
  • FLIR Lepton 3.5
  • PureThermal Mini Pro JST-SR
  • ADXL357 Evaluation Board
  • Future microphone integration

Software

  • Linux
  • Python
  • OpenCV
  • FFmpeg
  • V4L2
  • Local Web UI
  • LLM/RAG stack (planned)

Links

GitHub: TBD

Demo: TBD

Documentation: TBD