Photogrammetry is experiencing an era of democratization mostly due to the popularity and availability of many commercial off-the-shelf devices, such as drones and smartphones. They are used as the most convenient and effective tools for high-resolution image acquisition for a wide range of applications in science, engineering, management, and cultural heritage. However, the quality, particularly the geometric accuracy, of the outcomes from such consumer sensors is still unclear. Furthermore, the expected quality under different control schemes has yet to be thoroughly investigated. This paper intends to answer those questions with a comprehensive comparative evaluation. Photogrammetry, in particular, structure from motion, has been used to reconstruct a 3D building model from smartphone and consumer drone images, as well as from professional drone images, all under various ground control schemes. Results from this study show that the positioning accuracy of smartphone images under direct geo-referencing is 165.4 cm, however, this could be improved to 43.3 cm and 14.5 cm when introducing aerial lidar data and total station surveys as ground control, respectively. Similar results are found for consumer drone images as well. For comparison, this study shows the use of the professional drone is able to achieve a positioning accuracy of 3.7 cm. Furthermore, we demonstrate that through the combined use of drone and smartphone images we are able to obtain full coverage of the entire target with a 2.3 cm positioning accuracy. Our study concludes that smartphone images can achieve an accuracy equivalent to consumer drone images and can be used as the primary data source for building facade data collection.

The proliferation of Unmanned Aircraft Systems (UAS) in the United States National Airspace System (NAS) has resulted in an increasing number of close encounters between manned aircraft and UAS, which correlates with the increasing number of remote pilots in the Federal Aviation Administration (FAA) airmen database. This research explores spatial patterns of registered airmen using Geographic Information Systems (GIS) analyses that provide notable spatial distribution patterns of pilots and how they relate to UAS sightings and airspace categories. The application of GIS to these aviation data may assist safety practitioners with identifying geographic patterns, areas of higher risk, and ultimately improve safety management. The authors analyzed publicly available airmen data to examine spatial distribution patterns, data correlations, and inferences. Airmen addresses were first geocoded into ArcPro 10.4 GIS software as a vector data layer containing attribute values of the database. The spatial analysis tool set was then utilized to establish clustering, density patterns, and spatial relationships between various categories of registered airmen. These density analyses revealed implicitly that commercial registered pilots tend to have the highest clustering near major commercial use controlled airspace, yet registered remote (UAS) pilots are also clustered in these and other densely populated areas. UAS sighting data were also geocoded using zip code values of the reported city to potentially correlate UAS sighting with registered remote pilots, yet the lack of spatial precision in the database made establishing any type of spatial relationship ineffective. The implicit spatial relationships between commercial and remote registered pilots revealed further research is needed to integrate UAS safely and effectively into the national airspace. The poor quality of UAS sighting data also demonstrates the need to better utilize GIS to monitor and track UAS flights within the context of an Unmanned Traffic Management System.

Objective: Unmanned Aircraft System (UAS) pilots must possess a variety of cognitive skills in order to successfully perform diverse missions. They must accurately assess situations, make judgments and decisions, understand cues that may not be immediately obvious, and develop effective solutions. How may we gain perspective on how UAS pilots make decisions when higher order cognitive skills are needed to solve problems and accomplish their missions? Background: Previous UAS task analyses, both behavioral and cognitive, have seldom examined experienced, high-hour UAS operators. It is important to know how these pilots address and solve problems to improve training and design. METHOD: The Applied Cognitive Task Analysis method (ACTA) was utilized to define and examine a sampling of the cognitive task requirements of operating a civilian UAS. The task analysis included sixteen UAS journeymen and expert pilots who had between 240 and 2000 + hours of experience. Tasks such as communication, search and rescue mission planning, coping with equipment malfunction, and developing situational awareness of their environment were analyzed. Result: The analysis produced six task diagrams, which identified key cognitive considerations, captured pilot insights after flying simulated missions, and documented examples where pilots used their expertise to solve operational problems. Conclusion: This ACTA method and resulting products may contribute to the design of new training courses/programs for novice UAS pilots.

The European Union Aviation Safety Agency (EASA) continues to promulgate Safety Management Systems (SMS) across aviation organizations when it recently issued SMS requirements for EASA certificated Part 145 maintenance, repair and overhaul (MRO) organizations and Part 21 Design & Manufacturing (D&M) organizations. Currently, the Federal Aviation Administration (FAA) has no such rule in place for these U.S.-based organizations, which may challenge those doing business in countries where EASA policies apply. Given that a majority of the United States’ D&M and MRO population is made up of smaller organizations, it is likely a U.S. SMS regulation will require justification of the associated costs and benefits. This study explored the potential benefits SMS may provide these organizations by exploring the overall scope and nature of safety controls implemented through Airworthiness Directives (AD), which may help safety practitioners better understand how SMS in D&M organizations may reduce the number of AD related corrective actions. Researchers analyzed a sample of 189 ADs issued over a ten year period and found that approximately 55% of the sampled ADs were the result of a new risk control and approximately 45% were the result of a revised risk control. In these cases, the risk controls were not sufficient, and the AD action was necessary to ensure an acceptable level of safety. More effective risk controls have the potential to significantly reduce the number of ADs the industry must address. Every AD involves unplanned costs, often at multiple levels, and other variables that must be managed and implemented as part of the aircraft maintenance and manufacturing process. SMS may further improve the industry’s safety performance by reducing the number of corrective actions and their associated costs.

As the number of Uncrewed Aircraft Systems (UAS) operating in our National Airspace System (NAS) increases, so do UAS operations near or at an airport. The accelerating technology in Advanced Air Mobility (AAM) and related business opportunities will only further increase UAS operations at airports. This continued growth in new UAS technologies and applications introduces new hazards and risks to the airport environment. This proliferation of UAS highlights the importance of airports developing a robust Safety Management System (SMS) that includes specific UAS risk mitigations. There is currently little empirical data regarding UAS traffic around airports and there is no system established to collect this data at a national level. This study provides insight into UAS operations across a broader airport population by surveying airport managers in the United States (U.S.). Research results found that 62% of airports surveyed are experiencing an increase in UAS operations near their airports. This increase applies to all airspace classifications, with 67% of airports located in Class B, C, D controlled airspace experiencing increased UAS operations. Although the majority of airports have experienced increasing UAS operations, only 27% of airports have a UAS safety plan. Similarly, an increase in adverse UAS events reported near airports suggests that UAS operators may also lack robust safety plans, or an understanding of the risks and regulations associated with operating near airports.

Aircraft technicians perform visual inspections that include the processes of initiate, access, search, decision, response, and return. These processes are prone to human error, as they occur within complex socio-technical systems and dynamic environments. To address a technician’s human error, numerous technological solutions have been developed, often based on lessons learned from past accidents. However, these technological developments are effective only for the targeted tasks, and the existing frameworks do not comprehensively account for resource usage and lack intuitive clarity. Therefore, the researchers developed three Unified Modeling Language (UML) sequence based aircraft visual inspection frameworks designed to intuitively present the inspection processes and serve as a foundation for the development of emerging technologies that may improve a technician's inspection performance. Researchers conducted an extensive literature review on aircraft maintenance and inspection and interviewed 43 aircraft technicians. These efforts aimed to better understand the typical visual inspection processes technicians perform. From this data, researchers identified four key resources that technicians interact with during the visual inspection process and developed three frameworks using the UML to illustrate these interactions in a structured manner. From the frameworks, researchers propose a set of emerging technology tools. These include general tools applicable across all inspection stages, and specialized tools tailored for specific inspection processes. The proposed tools aim to improve a technician's inspection efficiency and accuracy, reducing human error, and may serve as a framework for integrating emerging technologies into visual inspection processes.