Challenges and Opportunities of Machine Learning and Deep Learning Techniques for the Internet of Drones

Abstract

The term IoD originates from internet of things (IoT), drones replace things. The term IoD is introduced in the autonomous flying robot or machine to make drones smarter. The internet of drones (IoD) is a layered framework control building organized generally for arranging the passage of unmanned aeronautical vehicles to controlled airspace and giving course organization between zones suggested as center points. Artificial intelligence (AI) is a term used straightforwardly in the drone business: anyway, Now human-made think AI is used in drones to make this flying machine increasingly splendid. In collaboration of drones to IoD, it will make, the existing sectors intelligent and smarter to work. Many studies have been utilized the power of supervised, semi-supervised, unsupervised machine learning (ML) and deep learning (DL) algorithms and the IoD to extract useful information from various sector where we can use application of IoD. ML, DL and IoD are the only two fields which when both applied together are able to give solutions to solve the real-world problems. This study focuses on the significant research in the area of smart drones. We will find the various algorithms of ML, deepfake, GAN, and DL. We also compare the performance of various algorithms in terms of computational performance which will make more smart drones. So, findings of this study are helpful for various application field of drones.