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Smart Fire Detecting System | SolidWorks, Raspberry Pi, ESP32, Python, Raspberry Pi, YOLOv8

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Arjun

Project Timeline

Oct 2025 - Nov-2025

OVERVIEW

Developed an autonomous vision-guided fire detection and suppression system capable of locating, tracking, and extinguishing ignition points with high precision. The system integrates a Raspberry Pi running a YOLOv8-based fire-detection model, a Pi Camera for real-time vision input, and an ESP32-controlled two-axis servo turret that automatically aligns and activates a targeted water jet. Mechanical components were fully CAD-modeled in SolidWorks and fabricated using PETG 3D printing, supported by engineering drawings, tolerance planning, and a complete Bill of Materials. Future implementation can incorporate AI-based fire-class classification to distinguish electrical, grease, chemical, and other fire types, enabling the system to automatically select the appropriate extinguisher medium for safer and more effective suppression. The final prototype demonstrates a complete end-to-end mechatronics system with reliable detection, targeting, suppression, and sweep-mode environmental scanning.

HighlightS

  • Delivered a fully functional autonomous fire suppression prototype capable of detecting and tracking fire in real time.
  • Achieved smooth and responsive targeting via closed-loop camera feedback and servo control.
  • Demonstrated precise water-jet actuation that reduces collateral damage compared to traditional sprinkler systems.
  • Successfully resolved mechanical tolerance issues, electrical layout constraints, and detection-accuracy challenges through iterative design and testing.
  • Presented a scalable concept that can be adapted for industrial and commercial fire-safety applications.


SKILLS

SolidworksComputer VisionRaspberry PiESP32PythonEmbedded SystemsRapid Prototyping
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