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Fire_Smoke_Detection_ML_MODEL

FireSight Guardian App - Vision-Based Smoke Detection & Alert System

This project was my final year university project.

An innovative smoke detection system prioritizing fast response times, affordability, and scalability. The system utilizes low-cost ESP32-CAM modules with built-in Wi-Fi and microcontrollers to capture live video streams, with basic image preprocessing handled on-device. These modules are strategically placed for comprehensive area coverage. It is not necessary to use an ESP32-CAM; any IP camera connected to the WLAN will suffice.

Smoke detection is performed using a lightweight YOLOv5s6 model processed on a central computer (with Jetson Nano as an option for real-world scenarios). The system delivers swift alerts via local alarms or smartphone notifications. Optional features for further development include GSM modules for uninterrupted transmission in weak Wi-Fi areas and solar power for extended outdoor deployments. Additional enhancements include flame location tracking, redundant detection frame removal, and intelligent delay mechanisms for improved accuracy and efficiency.

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Final year project - Fire Detection using YOLOv5 & ESP32-CAM with IOT notification

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