Point cloud data is a way of implementing and recreating the surrounding with the help of 3D imaging and rendering. These point clouds can be further converted into mesh and then 3d models that can be used for localisation and mapping. LIDAR (Light Detection and Ranging) is a common device that is used when we want to reconstruct a space(room or building) in a software 3D Mesh however LIDAR based systems are expensive and can be tricky to stitch and reconstruct, the proposed system uses a single camera, this single camera is going to capture the frame in a continuous manner. This frame capturing will be followed by feature extraction which is essentially going to help in comparing the motion of the camera by comparing the transformation of the frames relative to the previous frame. This process when implemented over a continuous frame path is going to help us build a 3D Space with the help of a process called photogrammetry. This can then be used in spatial planning or areas where the possibility of using lidar is not possible or the cost is too high for implementation. The estimated size from the sensor usually only differs a few centimeters from manually measured sizes. From 24 images the drone can generate more than 12000 feature points for photogrammetry and a point cloud with almost 10000 points for a room with a lot of features.