There are 4 repositories under smoke-detection topic.
fire-smoke-detect-yolov4-yolov5 and fire-smoke-detection-dataset 火灾检测,烟雾检测
Detect fire in images using neural nets
D-Fire: an image data set for fire and smoke detection.
An experimental repository to build ML models and perform efficient wildfire smoke detection.
Fire and smoke detection using spatial and temporal patterns.
Machine Learning in Python to assess fire risk in satellite imagery and environmental conditions.
Pipeline to train a multi-label smoke detection network. Code submission for the ProjectX 2020 machine learning competition.
Deep Learning-Based Fire Vehicle Detection and Real-Time Warning System 基於深度學習的火災車輛偵測及即時預警系統
A descriptive and inferential statistical analysis from the Kaggle database on the data collected by an IoT smoke detection device. Machine learning techniques were also used to help build this smart device, increasing its accuracy.
Research Internship project under Assistant Prof. Manish Bhatt of IIT, Guwahati
In this project, we will develop a system that monitors the temperature, humidity, smoke leakage, current voltage, and vibration of the server room via an Arduino IoT dashboard. In addition to attempting to detect and alert for Power Failure, Fire, Smoke, etc., this system will also integrate automation at the edge level for temperature control.
A superset of various wildfire smoke datasets.
Smoke Detection using Arduino UNO, MQ-2 sensor and Pico Buzzer.
🎥🌲🔥 Improving wildfire smoke detection models by creating virtual fine-tuning data in Unreal Engine.
Arduino-based smart home automation system or smart industry system that used a smoke sensor that can sense gas hazard gas and send feedback to the user or control room also adds a fire sensor that can sense fire in the home or industry and send message to the fire service department and save the home or office
Hello everyone , the name of this mini project is "SMOKE DETECTION USING ARDUINO" which comes under IOT(Internet of Things).
Modelling code for my Smoke Detection project.
Project Recognizing Industrial Smoke Emissions
A comparative analysis of traditional classification models (specifically Logistic Regression, K-Nearest Neighbours, Support Vector Classifier, Naïve-Bayes, eXtreme Gradient Boosting and Random Forest) for Smoke Detection dataset.
IoT-based system for real-time monitoring of temperature, air humidity, and pressure with the support of smoke detection
smoke and fire detector 🔥🚨