An advanced desktop-based smoke detection system using computer vision and a modern PyQt6 GUI. Designed with scalable architecture, real-time monitoring, and production-ready modular structure. Suitable for smart buildings, warehouses, offices, and IoT integration projects.

Generate image classifier

Project Recognizing Industrial Smoke Emissions

This repository contains the code and documentation for a Smart Room Automation System built with Arduino. Features include secure password-protected door access, occupancy-based lighting, and prioritized smoke detection with an exhaust fan. Simulated in Tinker Cad.

Modelling code for my Smoke Detection project.

smoke and fire detector 🔥🚨

IoT-based system for real-time monitoring of temperature, air humidity, and pressure with the support of smoke detection

FANS (Fire Alarm Notification System) is a distributed fire detection and emergency notification system built for the SYSC3010 Computer Systems Development project course.

ESP32-based Fire & Smoke Detection System using Flame Sensor, MQ-2, DHT11, Blynk IoT, and a Python serial listener for automatic image capture on fire detection.

The MVP provides automated fire risk assessment by extracting wildfire indicators—such as smoke, flame patterns, and thermal anomalies—from imagery, and presenting them in structured natural language analysis.

Hello everyone , the name of this mini project is "SMOKE DETECTION USING ARDUINO" which comes under IOT(Internet of Things).

Smart fire and smoke detection using YOLO on a Raspberry Pi with IoT integration. The system identifies fire and smoke from images, achieving 90.2% accuracy for fires and 85.7% for smoke. Demonstrates the power of machine learning and automation in real-time safety monitoring.

Explainable AI and YOLOv8-based Framework for Indoor Fire and Smoke Detection

AI-powered no-smoking detection system using Raspberry Pi, OpenCV, OLED display, and smoke sensor with real-time alerts and web dashboard.

Indoor Fire and Smoke Detection using Soft-Voting based Deep Ensemble Model

Гибридная система обнаружения огня и дыма на EfficientNet + YOLOv5. Оптимизирована для CPU, работает в реальном времени.

Low-cost wildfire monitoring using IoT sensors, edge computer vision, and deep reinforcement learning.

Smoke Detection using Arduino UNO, MQ-2 sensor and Pico Buzzer.

Real-time fire and smoke detection using YOLOv11 (Ultralytics) with webcam inference and training notebook.

Nature inspired firefighter assistant by Unmanned Aerial Vehicle (UAV) data