Internet of Things (IoT): Wireless Communications for Unmanned Aircraft System

Abstract

In times of technological advancements, the use of aerial vehicles (UAVs), commonly known as drones, has become increasingly prevalent across various commercial and industrial sectors. UAVs find applications in agriculture, filmmaking, law enforcement, package delivery, aerial photography, videography, etc. There are benefits associated with utilizing UAVs. One key advantage is their ability to cover areas quickly and efficiently while accessing locations that may be challenging or hazardous for humans. Wireless communication technologies play a role in ensuring the functioning of Unmanned Aircraft Systems (UAS). Without these technologies, the United States of America would face difficulties communicating with ground control stations or relaying information to operators. This would significantly impede the country’s mission execution and overall responsibilities. Wireless communication technologies (WCT) enable the United States to maintain awareness—essential for achieving successful and secure operations. Additionally, wireless technologies allow for Unmanned Aerial Systems (UAS) control, which is crucial for missions carried out in hostile or dangerous environments. The increasing usage of drones has highlighted the need to improve networks in the United States focusing on their ability to work together effectively handle volumes of data and provide reliable broadband connectivity. This research delves into communication technologies, in this domain emphasizing their advantages, limitations, industry standards and potential areas for future investigation to address the challenges revealed by this study.

Condition Monitoring of Pneumatic Drive Systems Based on the AI Method Feed-Forward Backpropagation Neural Network

“…Condition-based maintenance (CBM) is a maintenance program that collects process data in real-time (called condition monitoring—CM) to intercept phenomena that can lead to failures so that operators and manufacturers can make informed maintenance decisions to maintain machine availability, reliability, and performance. CBM can be applied to a variety of systems: general mechanical systems with shafts, gears, bearings [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ], aircrafts [ 12 ], actuators [ 13 , 14 ], wind turbines [ 15 , 16 , 17 ] etc. CBM is generally based on diagnostics and/or prognostics: in the former, anomalies in process data caused by incipient failures are identified; in the latter, failures are predicted before they occur.…”