PyroCyclone Eye: Satellite Detection System For Wildfire And Cyclone

Cyclones and wildfires are deadly; they do significant damage to human life and property. This requires an effective early warning system that would ensure a timely intervention since the normal methods are not efficient. Frequently fall short of the necessary pace and precision in successful detection as well as signaling: this results in response lag times and escalation of loss. In addition, most current systems often work on their own without any cooperation. It lacks integration and immediate communication means to the concerned authorities. However, in this study, we put forward a novel system that combines detection with early warning for cyclones and wild fires through satellite images using advanced computer vision techniques. We apply the YOLOv9 object detection algorithm on the satellite pictures which allows us to detect cyclones and wildfires with a high level of precision as well as speed. In addition, we design an alert system Using the Twilio WhatsApp API to report detected incidents to the relevant authorities without delay. Through this we aim to improve disaster management potential minimizing loss to life and property and ensure safety to the communities vulnerable to natural disasters.