Augmented Reality based navigation during Climate emergencies and crises.

We propose a novel augmented reality (AR) navigation methodology for buildings during emergency situations. The methodology addresses the challenges of existing AR navigation applications, which typically use pre-existing map models and are not able to provide accurate navigation instructions in real-time. The proposed methodology uses a combination of A* algorithm, YOLO, an object detection machine learning algorithm, and PlaceNote SDK to overcome these challenges. The A* algorithm finds the shortest path to the nearest exit, while YOLO detects objects such as stairs, elevators, and other obstacles in the user's path. PlaceNote SDK builds a real-time map of the building, which allows the application to track the user's location and provide accurate navigation instructions, even in low-visibility conditions. In this paper, we shall further elaborate on the framework used to establish a safe and fast Augmented Reality based navigation experience for emergencies.