UAS in the Airspace: A Review on Integration, Simulation, Optimization, and Open Challenges

Air transportation is essential for society, and it is increasing gradually due to its importance. To improve the airspace operation, new technologies are under development, such as Unmanned Aircraft Systems (UAS). In fact, in the past few years, there has been a growth in UAS numbers in segregated airspace. However, there is an interest in integrating these aircraft into the National Airspace System (NAS). The UAS is vital to different industries due to its advantages brought to the airspace (e.g., efficiency). Conversely, the relationship between UAS and Air Traffic Control (ATC) needs to be well-defined due to the impacts on ATC capacity these aircraft may present. Throughout the years, this impact may be lower than it is nowadays because the current lack of familiarity in this relationship contributes to higher workload levels. Thereupon, the primary goal of this research is to present a comprehensive review of the advancements in the integration of UAS in the National Airspace System (NAS) from different perspectives. We consider the challenges regarding simulation, final approach, and optimization of problems related to the interoperability of such systems in the airspace. Finally, we identify several open challenges in the field based on the existing state-of-the-art proposals

Deep Learning in Air Traffic Management (ATM): A Survey on Applications, Opportunities, and Open Challenges

Currently, the increasing number of daily flights emphasizes the importance of air transportation. Furthermore, Air Traffic Management (ATM) enables air carriers to operate safely and efficiently through the multiple services provided. Advanced analytic solutions have demonstrated the potential to solve complex problems in several domains, and Deep Learning (DL) has attracted attention due to its impressive results and disruptive capabilities. The adoption of DL models in ATM solutions enables new cognitive services that have never been considered before. The main goal of this research is to present a comprehensive review of state-of-the-art Deep Learning (DL) solutions for Air Traffic Management (ATM). This review focuses on describing applications, identifying opportunities, and highlighting open challenges to foster the evolution of ATM systems. To accomplish this, we discuss the fundamental topics of DL and ATM and categorize the contributions based on different approaches. First, works are grouped based on the DL approach adopted. Then, future directions are identified based on the ATM solution area. Finally, open challenges are listed for both DL applications and ATM solutions. This article aims to support the community by identifying research problems to be faced in the future

Teaching Digital Electronics during the COVID-19 Pandemic via a Remote Lab

Practical knowledge is essential for engineering education. With the COVID-19 pandemic, new challenges have arisen for remote practical learning (e.g., collaborations/experimentations with real equipment when face-to-face offerings are not possible). In this context, LabEAD is a remote lab project that aims to provide practical knowledge learning opportunities for Brazilian engineering students. This article describes how engineering project management methods consisting of application domains, requirement identification, technical solution specification, implementation, and delivery phases, were applied to the development of an Internet of Things (IoT) remote lab architecture. The distributed computing environment allows integration between students’ smartphones and IoT devices deployed in campus labs and in student residences. The code is open-source for facilitated replication and reuse, and the remote lab was built in six months to enable six experiments for the digital electronics lab during the COVID-19 pandemic, covering all the experiments of the original face-to-face offering. More than 70% of the 32 students preferred remote labs over simulations, and only 2 were not approved in the digital electronics course offered remotely.Student perceptions collected by questionnaires showed that they could successfully specify, develop, and present their projects using the remote lab infrastructure in four weeks