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The Internet of Flying Things (IoFT) plays a vital role in modern applications such as aerial surveillance and smart mobility. However, it remains highly vulnerable to cyberattacks that threaten the confidentiality, integrity, and…
Outsourcing data storage to the remote cloud can be an economical solution to enhance data management in the smart grid ecosystem. To protect the privacy of data, the utility company may choose to encrypt the data before uploading them to…
Deploying robot learning methods to aerial robots in unstructured environments remains both challenging and promising. While recent advances in deep reinforcement learning (DRL) have enabled end-to-end flight control, the field still lacks…
We present an energy-efficient anti-UAV system that integrates frame-based and event-driven object tracking to enable reliable detection of small and fast-moving drones. The system reconstructs binary event frames using run-length encoding,…
Optimization problems with drones are widely studied in a variety of civilian tasks, mainly due to their ability to traverse rough terrains and to carry cameras and other sensors for surveillance tasks. The limited battery life of these…
Drones will have extensive use cases across various commercial, government, and military sectors, ranging from delivery of consumer goods to search and rescue operations. To maintain the safety and security of people and infrastructure, it…
The adoption of Uncrewed Aerial Vehicles (UAVs) for last-mile deliveries will affect the energy productivity of package delivery and require new methods to understand the associated energy consumption and greenhouse gas (GHG) emissions.…
Secure communication is a critical requirement for Internet of Things (IoT) devices, which are often based on Microcontroller Units (MCUs). Current cryptographic solutions, which rely on software libraries or dedicated hardware…
The growing deployment of drones in a myriad of applications relies on seamless and reliable wireless connectivity for safe control and operation of drones. Cellular technology is a key enabler for providing essential wireless services to…
Data compression combined with effective encryption is a common requirement of data storage and transmission. Low cost of these operations is often a high priority in order to increase transmission speed and reduce power usage. This…
In the 21st century, the industry of drones, also known as Unmanned Aerial Vehicles (UAVs), has witnessed a rapid increase with its large number of airspace users. The tremendous benefits of this technology in civilian applications such as…
This paper addresses the problem of autonomous task allocation by a swarm of autonomous, interactive drones in large-scale, dynamic spatio-temporal environments. When each drone independently determines navigation, sensing, and recharging…
Present-day Deep Reinforcement Learning (RL) systems show great promise towards building intelligent agents surpassing human-level performance. However, the computational complexity associated with the underlying deep neural networks (DNNs)…
In this paper, we present a load-balancing approach to analyze and partition the UAV perception and navigation intelligence (PNI) code for parallel execution, as well as assigning each parallel computational task to a processing element in…
Unmanned aerial vehicles (UAVs) can provide wireless access services to terrestrial users without geographical limitations and will become an essential part of the future communication system. However, the openness of wireless channels and…
Unmanned Aerial Vehicles (UAVs) are integral in various sectors like agriculture, surveillance, and logistics, driven by advancements in 5G. However, existing research lacks a comprehensive approach addressing both data freshness and…
This paper studies the feasibility of supporting drone operations using existent cellular infrastructure. We propose an analytical framework that includes the effects of base station (BS) height and antenna radiation pattern, drone antenna…
The formation trajectory planning using complete graphs to model collaborative constraints becomes computationally intractable as the number of drones increases due to the curse of dimensionality. To tackle this issue, this paper presents a…
Swarms of drones offer an increased sensing aperture, and having them mimic behaviors of natural swarms enhances sampling by adapting the aperture to local conditions. We demonstrate that such an approach makes detecting and tracking…
Deep neural networks (DNNs) are currently widely used for many artificial intelligence (AI) applications including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at…