Fire detection plays the crucial role in today generation to overcome this problem we build a fire detection system that helps to take safety measures. Our aim is building the project without using traditional methods like flame sensors and smoke sensors because the are costly and less speed and accuracy. Our proposed system uses YOLOv8 algorithm which helps to detect fire quickly and accurately. And, the other problem was alerting module they are so many fire detection systems in the world with less alerting module. In our system we used twilio library which helps to improve alerting modules after detecting fire with confidence score>0.5 the system triggers and make loud noise then send the text message, whats app message with monitored location also notify with phone call.
Fire detection with immediate alert using YOLOv8 involves leveraging the advanced object detection capabilities of the YOLOv8 model to identify fire instances in video feeds. This system quickly processes incoming data, detects fire, and sends immediate alerts to relevant parties or systems for rapid response. YOLOv8's high accuracy and speed make it suitable for real-time fire detection in various settings, such as buildings and industrial areas. Intigrate this technology with existing CCTV cameras that can useful for taking saftey measures before any large fire incidents accurs.
At initial stage we have to collect images for training and testing purpose with yolo model.
then split the data into training and validation.
Then train the images with annotating the fire instances with bounding boxes.
deploy the project with yolov8 model in python ide and run the module.
we got expected result from the sytem after running the project.
At the end in alerting module the system sends the map was not accurate because of we not add Google map API which not available for free but we did with what we have.
Working thing was after fire detection the sytem alert with sound and notify the authorized users with phone call, SMS and Whatsapp message with google map link(The link of the google map was not much accurate but it shows nearby locations).
Thank You :)