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 primary threat rice production, decreasing yield, quality. assessment tedious task requires heavy labor long duration due the vast land areas involved. Newly developed autonomous scouting techniques have shown promise mapping fields without any human interaction. By combining lodged detection edge computing, it possible estimate...

Smart agriculture benefits from unmanned aerial vehicles (UAV), and in-field sensors to collect data used make responsible crop management decisions which sustainably increase yields. In addition, smart relies on machine learning algorithms, creative networking solutions, edge cloud computing resources collect, transfer, process agricultural data. UAV can carry a wide array of sensors, maneuver rapidly throughout the field, apply treatments for some health problems, be flown by software....

Unmanned aerial systems (UAS) are increasingly used in precision agriculture to collect crop health related data. UAS can capture data more often and cost-effectively than sending human scouts into the field. However, large fields, flight time, hence collection, is limited by battery life. In a conventional approach, operators required exchange depleted batteries many times, which be costly time consuming. this study, we developed novel, fully autonomous scouting approach that preserves life...

Fully autonomous aerial systems (FAAS) fly complex missions guided wholly by software. If users choose software, compute hardware and aircraft well, FAAS can complete faster safer than unmanned piloted humans. On the other hand, poorly managed edge resources slow down missions, waste energy inflate costs. This paper presents a model-driven approach to manage FAAS. We real profile resource usage model expected demands. Naive profiling approaches use traces from previous flights infer usage....

Precision agriculture examines crop fields, gathers data, analyzes health and informs field management. This data driven approach can reduce fertilizer runoff, prevent disease increase yield. Frequent collection improves outcomes, but also increases operating costs. Fully autonomous aerial systems (FAAS) capture detailed images of fields without human intervention. They costs significantly. However, FAAS software must embed agricultural expertise to decide where fly, which when land. paper...

Unmanned Aerial Vehicles are powerful robotic tools capable of quickly sensing vast areas. Their maneuverability and speed suit them to tasks in diverse domains including agriculture, search rescue, infrastructure inspection, ecology. Piloting these missions, however, is expensive, time consuming, requires expertise. Furthermore, environments for can be large, necessitating swarms UAV timely scouting. Waypoint-based automated collection systems have existed over a decade, but rarely account...

Automation is utilized heavily in many domains to increase productivity. With new, more complex automation, like the self-driving car, humans will be required forego direct task performance favor of maintaining a supervisory role over automation systems. While use these systems generally results greater than performing alone, are reluctant adopt superior due lack trust. The United States Department Defense investigating trust order influence rate adoption technology. Studying requires...

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 ability approximate complex non-linear functions. Despite their effectiveness, they generally require large labeled data sets considerable processing power for both training prediction. Some these bottlenecks been mitigated by increased availability high-quality sets, improvements network development software,...

Digital agriculture, hailed as the fourth great agricultural revolution, employs software-driven autonomous agents for in-field crop management. Edge computing resources deployed near fields support with substantial computational needs tasks such AI inference. In large fields, using multiple agents, called swarms, can speed up management if sufficient edge are provisioned. However, to use swarms today, farmers and software developers craft their own standalone solutions that either simple...

Control firmware in unmanned aircraft systems (UAS) manage the subsystems for in-flight dynamics, navigation and sensors. Computer on-board on gateway machines can now support rich features control firmware, such as GPS-driven waypoint missions autonomy. However, source code behind harbor software bugs whose symptoms are detectable only during flight. Often, UAS have serious that lead to dangerous situations. We studied previously reported open-source repositories of ArduPilot PX4, two...

Neuromorphic computing hardware mimics neurobiological architectures and promises eventual low power operation. Additionally, arbitrary waveform generator permits the realization of complex radar structures. In this paper, we combine these two technologies investigate potential spiking neural networks to generate waveforms their suitability in dynamic environments where adaptability is paramount. We discuss process development, current limitations, critical assumptions realizing real-time...

Vehicular Ad-Hoc networks depend on clear communication between vehicles using radio frequency in order to operate effectively. Interference from existing technologies the RF spectrum, e.g. IoT devices, UAV, mobile systems, calls into question feasibility of future VANET systems without an ability cut through noise. One approach overcome interference is use waveform design provide this capability. Regrettably, most traditional algorithms are too computationally complex perform efficiently...

Fully autonomous aerial systems (FAAS) are an increasingly relevant research topic to the computer community [1] –[6]. FAAS use unmanned vehicles and edge cloud compute resources dynamically sense respond their environments without human piloting. can be used in crop scouting, photography, search rescue, infrastructure inspection, many other domains.

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, more. In response to this popularity, UAV manufacturers, hobbyists, researchers have developed myriad software packages control simplify automate flight. Recent advances also led autonomous that complete complex missions without human pilots swarms work together solve tasks....

Unmanned aerial vehicles (UAV) play a critical role in many edge computing deployments and applications. UAV are prized for their maneuverability, low cost, sensing capacity, facilitating applications that would otherwise be prohibitively expensive or dangerous without them. cheaper than alternative analysis methods, but still incur costs from human piloting workloads which necessitate high-resolution coverage of large areas. Recently, autonomous swarms have emerged to increase the speed...

Edge computing is a growing paradigm where compute resources are provisioned between data sources and the cloud to decrease latency from transfer, lower costs, comply with security policies, more. systems as varied their applications, serving internet services, IoT, emerging technologies. Due tight constraints experienced by many edge systems, research testbeds have become valuable tools for application benchmarking. Current testbed infrastructure, however, fails properly emulate important...

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 is possible with current technology, but extant techniques can not meet real-time latency requirements on low size weight power (SWaP) embedded hardware ideal for contexts where online most useful. Current rely convex optimization, leading to non-trivial execution times...

Autonomous systems (AS) carry out complex missions by continuously observing the state of their surroundings and taking actions toward a goal. Swarms AS working together can complete faster more effectively than single alone. To build swarms today, developers handcraft own software for storing, aggregating, learning from observations. We present Fleet Computer, platform developing managing swarms. The Computer provides programming paradigm that simplifies multi-agent reinforcement (MARL) --...

Unmanned aerial vehicles (UAVs) are gaining popularity in many governmental and civilian sectors. The combination of mobility data sensing capabilities facilitates previously impossible workloads. UAVs normally piloted by remote operators who determine where to fly when sense data, but operations over large areas put a heavy burden on human pilots. Fully autonomous systems (FAAS) have emerged as an alternative piloting using software combined with edge cloud hardware execute UAV missions....

Internet of Things (IoT) and Edge deployments are diverse, complex, 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 IoT deployments. Our uses the PROWESS testbed accurately emulate candidate form-factors, optimizes parameters minimize costs. show that our finds optimal configurations 6.3X faster than Bayesian optimization, state art hyperparameter optimization technique.

Unmanned aerial vehicles (UAV) enable novel but demanding computational workloads that exceed processing capacity of their onboard resources. Mobile and edge devices can support workloads, they increase network communication power usage. These resource constraints block potentially transformative UAV applications execute too slowly or use much power. This poster presents early efforts to characterize demands emerging applications. We are building a selfie-drone benchmark. Our benchmark will...