Create an app that will enable small drone operators to know more about specific weather parameters, local terrain and no fly zones within a five-mile radius of their GPS location.
It's an idea to solve both the problem with the internet connection by reducing the white zone and avoiding drone's acidents. For that we should maintain the longest period of flight and that will be possible thanks to the blimp. In fact, this project is a combination Between a blimp that will Maintain the endurance Of flight and a quadcopter that provides dynamic mouvement. Besides, the application will be developed on Java programmation and it will have the access to the internet thanks to the internet provided by the shield installed in the blimp-quadcopter. So, it will connect to the NASA Database that describes the weather, wind speed, No-fly zones, the GPS and import those data. First, it imports the GPS map. Then, we select the zone by drawing a circle (five-mile radius) using the Bresenham algorithm collect the information in that zone on the 3 maps. The Data exploration will be based on the DATA mining (neural network) and machine-learning concepts. The machine-learning is used to optimize the algorithme. But before, the code must make a decision (the drone can fly in that zone or not). To make it happen, it will not only use the data imported from the internet, but also the blimp-quadcoptor configuration (its speed, weight, resistance..) to maintain its stability. This will be based on aerodynamic equations of both the blimp and the quadcopter). To make the decision, this application will use the decision tree concept. Once the decision made, the data and the decision will be saved in a virtual cloud related to the the blimp-quadcopter network as it’s going to be used by the machine-learning and that will save much time.