Bayesian Filtering-Based Internet of Drone Things for Precision Drone Delivery: Challenges, Unravelling, and Future Research Scope

Recent years have witnessed abundant growth in the Internet of Drone Things (IoDTs) in the field of communication, supervising drones, and several severe environmental situations, etc., and the last decade beheld the application of unmanned aircraft systems, called delivery drones, in performing logistics operations such as the delivery of pharmaceutical products, groceries, and other essential daily products. This article accounts for the apotheosis of IoDTs in precision drone delivery using the Bayesian filtering methods. We also discuss the challenges associated with the real-time scenario. Finally, it also includes research opportunities and the future scope of IoDTs based on Bayesian filtering for drone delivery applications.