Jayson Boubin

• Doctor of Philosophy
• Assistant Professor at Binghamton University

Edge deployments perform complex deep learning inference and analysis in the wild in highly resource constrained environment. They are positioned everywhere from our largest cities to the bottom of our oceans, and often necessitate significant financial resources and labor to create and deploy. These properties make correctness of edge deployments...

Unmanned Aerial Vehicles are powerful robotic tools capable of quickly sensing vast areas. Their maneuverability and speed suit them to sensing tasks in diverse domains including agriculture, search and rescue, infrastructure inspection, and ecology. Piloting these missions, however, is expensive , time consuming, and requires expertise. Furthermor...

Internet of Things (IoT) and Edge deployments are diverse, complex, and highly constrained. These properties make correctness difficult or impossible to verify a priori. We present early work on an automatic deployment right-sizing tool for edge and IoT deployments. Our tool uses the PROWESS testbed to accurately emulate candidate deployment form-f...

Digital agriculture, hailed as the fourth great agricultural revolution, employs software-driven autonomous agents for in-field crop management. Edge computing resources deployed near crop fields support autonomous agents with substantial computational needs for tasks such as AI inference. In large fields, using multiple autonomous agents, called s...

Unmanned aerial vehicles (UAV) are revolutionizing critical industries. Their inexpensive and accessible nature makes them useful for a number of broad applications including agriculture, infrastructure inspection, and more. In response to this popularity, UAV manufacturers, hobbyists, and researchers have developed myriad software packages for UAV...

Unmanned aerial vehicles (UAV) play a critical role in many edge computing deployments and applications. UAV are prized for their maneuverability, low cost, and sensing capacity , facilitating many applications that would otherwise be prohibitively expensive or dangerous without them. UAV are cheaper than alternative aerial analysis methods, but st...

Edge computing is a growing paradigm where compute resources are provisioned between data sources and the cloud to decrease compute latency from data transfer, lower costs, comply with security policies, and more. Edge systems are as varied as their applications, serving internet services, IoT, and emerging technologies. Due to the tight constraint...

Spectral notching, a waveform design method used in signal processing and radar, mitigates interference caused by an ever-growing number of technologies which saturate the radio frequency (RF) spectrum. Online wave-form design is possible with current technology, but extant techniques can not meet real-time latency requirements on the low size weig...

In recent years, neural networks have exploded in popularity, revolutionizing the domains of computer vision, natural language processing, and autonomous systems. This is due to neural networks ability to approximate complex non-linear functions. Despite their effectiveness, they generally require large labeled data sets and considerable processing...

Control firmware in unmanned aircraft systems (UAS) manage the subsystems for in-flight dynamics, navigation and aircraft sensors. Computer systems on-board the aircraft and on gateway machines can now support rich features in the control firmware, such as GPS-driven waypoint missions and autonomy. However, the source code behind control firmware c...

Autonomous systems (AS) carry out complex missions by continuously observing the state of their surroundings and taking actions toward a goal. Swarms of AS working together can complete missions faster and more effectively than single AS alone. To build swarms today, developers handcraft their own software for storing, aggregating, and learning fro...

Unmanned aerial vehicles (UAVs) are gaining popularity in many governmental and civilian sectors. The combination of aerial mobility and data sensing capabilities facilitates previously impossible workloads. UAVs are normally piloted by remote operators who determine where to fly and when to sense data. Fully autonomous aerial systems (FAAS) have e...

Unmanned aerial systems (UAS) are increasingly used in precision agriculture to collect crop health related data. UAS can capture data more often and more cost-effectively than sending human scouts into the field. However, in large crop fields, flight time, and hence data collection, is limited by battery life. In a conventional UAS approach, human...

Rice is a globally important crop that will continue to play an essential role in feeding our world as we grapple with climate change and population growth. Lodging is a primary threat to rice production, decreasing rice yield, and quality. Lodging assessment is a tedious task and requires heavy labor and a long duration due to the vast land areas...

Fully autonomous aerial systems (FAAS) are an increasingly relevant and intriguing research topic which require considerable systems support. FAAS use unmanned aerial vehicles and edge and cloud compute resources to dynamically sense and respond to their environments without human piloting. FAAS are useful in a number of domains, but are very diffi...

Resource-limited embedded devices like Unmanned Aerial Vehicles (UAVs) often rely on offloading or simplified algorithms. Feature extraction such as Principle Component Analysis (PCA) can reduce transmission data without compromising accuracy, or even be used for applications like facial detection. This involves solving eigenvectors and values whic...

Resource-limited embedded devices like Unmanned Aerial Vehicles (UAVs) often rely on offloading or simplified algorithms. Fea- ture extraction such as Principle Component Analysis (PCA) can reduce transmission data without compromising accuracy, or even be used for applications like facial detection. This involves solving eigenvectors and values wh...

Fully autonomous aerial systems (FAAS) fly complex missions guided wholly by software. If users choose software, compute hardware and aircraft well, FAAS can complete missions faster and safer than unmanned aerial systems piloted by humans. On the other hand, poorly managed edge resources slow down missions, waste energy and inflate costs. This pap...

Vehicular Ad-Hoc networks depend on clear communication between vehicles using radio frequency in order to operate effectively. Interference from existing technologies using the RF spectrum, e.g. IoT devices, UAV, mobile systems, calls into question the feasibility of future VANET systems without an ability to cut through the noise. One approach to...

Automation is utilized heavily in many domains to increase productivity. With new, more complex automation, like the self-driving car, humans will be required to forego direct task performance in favor of maintaining a supervisory role over automation systems. While the use of these systems generally results in greater performance than humans perfo...

Human-machine teaming is becoming an ever present aspect of executing modern military missions. In this paper, we discuss an extensive line of research currently being conducted at the Air Force Institute of Technology focused specifically on using simulation in the design of automated systems in order to improve human-automation interactions. This...