Influencing Factors for Use of Unmanned Aerial Systems in Support of Aviation Accident and Emergency Response

The purpose of this research paper was to examine the influencing factors associated with the use of unmanned aerial system (UAS) technology to support aviation accident and emergency response. The ability of first responders to react to an emergency is dependent on the quality, accuracy, timeliness, and usability of information. With aviation accidents such as the Asiana Airlines Flight 214 crash at San Francisco International Airport, the ability to sense and communicate the location of victims may reduce the potential for accidental passenger death. Furthermore, the ability to obtain information en-route to an accident may also to assist to reduce overall response and coordination time of first responders (e.g., Aviation Rescue and Firefighting [ARFF]). By identifying and examining current and potential practices, capabilities, and technology (e.g., human-machine-interface [HMI], human factors, tools, and capability modifiers) a more comprehensive model of the influencing factors is established to further support the growing body of knowledge (i.e., safety, human computer interaction, human-robot systems, socio-economical systems, service and public sector systems, and technological forecasting). A series of recommendations regarding the technology and application are provided to support future development or adaptation of regulations, policies, or future research. --from the article

Using Unmanned Aerial Vehicles for Wireless Localization in Search and Rescue

This thesis presents how unmanned aerial vehicles (UAVs) can successfully assist in search and rescue (SAR) operations using wireless localization. The zone-grid to partition to capture/detect WiFi probe requests follows the concepts found in Search Theory Method. The UAV has attached a sensor, e.g., WiFi sniffer, to capture/detect the WiFi probes from victims or lost people’s smartphones. Applying the Random-Forest based machine learning algorithm, an estimation of the user\u27s location is determined with a 81.8% accuracy. UAV technology has shown limitations in the navigational performance and limited flight time. Procedures to optimize these limitations are presented. Additionally, how the UAV is maneuvered during flight is analyzed, considering different SAR flight patterns and Li-Po battery consumption rates of the UAV. Results show that controlling the UAV by remote-controll detected the most probes, but it is less power efficient compared to control it autonomously

The case of Guarda Nacional Republicana

It is known that the quickness and effectiveness of Search and Rescue (SAR) missions are crucial to their success. This study has the purpose of understanding how the application of an Unmanned Aircraft System (UAS) in SAR missions, could bring improved outcomes and be an added value to the procedures that are already performed by SAR teams. In this study, the results were obtained by performing a series of field trials, based on the recreation of real SAR scenarios and the implementation of an operational plan proposal, with recordings of time lapses at different phases of the operation. The reports of the real scenarios were provided by the teams of the Grupo de Intervenção, Proteção e Socorro (GIPS), who are under the command of the Unidade de Intervenção (UI), specialized in this type of missions. Both GIPS and UI are dependent on Tenente General Comandante Geral of the Guarda Nacional Republicana (GNR). A survey developed by the National Aeronautics and Space Administration (NASA) was also applied at the end of each trial in order to evaluate the workload index of the participants in the trials. Throughout this research, conclusions are obtained taking into account the difference of an UAS operation between day and night periods, the improvements to the current procedures, but also the limitations of this system, such as the measures that should be taken when this system is applied in SAR missions. Conclusions were also based on the replies to the surveys. The focus of this case study was the use of an UAS in SAR missions performed in a mountain environment, well known by its adverse weather conditions. This study proved that, under these kinds of conditions, the use of the UAS was not always possible due to their own limitations and the validation of the proposed operational plan was obtained.Sabe-se que a rapidez e eficácia na realização de missões de busca e salvamento, são fatores cruciais para assegurar o seu sucesso. Um dos principais objetivos deste estudo é perceber se, a aplicação de um Unmanned Aircraft System (UAS), neste tipo de missões, pode ou não acarretar evoluções e por sua vez melhorias aos procedimentos já anteriormente realizados pelas equipas de busca e salvamento. Os resultados deste estudo foram alcançados através da realização de ensaios no terreno, tendo como base a recriação de cenários reais de busca e salvamento que tivessem já ocorrido. Através da implementação de uma proposta de plano operacional, foram também retirados diversos tempos de desempenho em diferentes fases da operação. Os relatórios dos cenários reais foram disponibilizados pelas equipas do Grupo de Intervenção, Proteção e Socorro (GIPS) que, estão sob o comando da Unidade de Intervenção (UI) especializadas neste tipo de missões. Tanto o GIPS como a UI estão dependentes do Tenente General Comandante Geral da Guarda Nacional Republicana (GNR). Foi também aplicado um inquérito desenvolvido pela National Aeronautics and Space Administration (NASA) para avaliar o índice de carga de trabalho dos participantes no final de cada um dos ensaios. Ao longo desta pesquisa, foram tiradas conclusões sobre a diferença na operação de um UAS entre o período diurno e noturno, as melhorias sentidas nos procedimentos usados atualmente, assim como as suas limitações e medidas que devem ser tomadas quando aplicado em missões de busca e salvamento. Também são retiradas conclusões a partir das respostas obtidas ao inquérito. Este caso de estudo tem, como foco, as missões de busca e salvamento realizadas em ambiente montanhoso bem conhecido pelas suas condições climatéricas adversas. Foi também verificado que na presença destas condições a aplicação de um UAS nem sempre é possível, devido as limitações próprias do equipamento e obteve-se a validação do plano operacional proposto

Application of UASs to augment ground surveys in cranberry agriculture development: a proof of concept for the integration of UAS into the site identification and monitoring of cranberry farms in Newfoundland

Assessing the potential for developing wetland environments into cranberry agricultural lands is time consuming and expensive. The addition of unmanned aerial systems (UAS) to augment current ground survey techniques has the potential to increase assessment accuracy and cranberry production while reducing costs. Newfoundland’s extensive wetlands offer significant opportunities for the development of cranberry agricultural lands. Due to a large international demand for raw cranberries, there is great potential economic benefit in the rapid development of cranberry farms. This study focused on using UASs to assess wetland areas in Newfoundland by applying suitability criteria developed by the Newfoundland Government. This was done through the use of GIS, image classification, and photogrammetry to assess these criteria over three site locations. The viability of expanding UAS data collection over larger areas to develop a province-wide model was explored through an assessment of current fixed wing UAS technology. Given the novelty of this area of study, this research aimed to serve as a proof of concept where the validity of results was measured against real world applicability, not statistical analysis. The results showed that because UASs cannot assess all of the required wetland criteria, they are not a viable replacement for current ground surveys, but do have the potential to augment current techniques. UASs make it possible to survey larger areas, as well as reduce time and cost. The assessment of current fixed wing UAS technology concluded that given the continuously improving technology and further testing, there is the potential for these systems to collect comparable data over a larger area. Overall, the study concluded that through the strategic integration of the UAS techniques developed in this study with existing ground survey methods, Newfoundland has the potential to increase cranberry agricultural development and capitalize on the global demand for this crop

A Behavioral Research Model for Small Unmanned Aircraft Systems for Data Gathering Operations

According to Hitlin (2017) of the Pew Research Center, only 8% of U.S. citizens own an unmanned aircraft. Additionally, regarding feelings if U.S. citizens saw an unmanned aircraft flying close to where they live, 26% say they would be nervous, 12% feel angry, and 11% are scared. As of March 9, 2018, there were 1,050,328 U.S. small unmanned aircraft system (sUAS) registrations compared to 947,970 November 29, 2017. While sUAS use has increased in the U.S., it has lagged when compared to other items for personal use available to U.S. citizens as 92% own cell phones (Anderson, 2015). This slower acceptance rate identifies a potential need for more research as to why. No studies have specifically focused on individual factors for the behavioral intention of using sUAS for data gathering, encompassing the variables used in this study, nor a Structural Equation Model that shows relevant factors and associated relationships. Also, current ground theories fall short, lacking appropriate variables or modeling ability. Thus, this dissertation study developed a new behavioral research model termed VMUTES to determine the factors that influenced individuals’ intentions to operate small sUASs for data gathering and relationships between those factors. A sUAS system is comprised of integrated hardware, software, processes, or firmware. Data gathering is defined in this study as the transmission or recording of audio, pictures, videos, or collection of other data for modeler, civil, or public use. The new VMUTES model integrates portions of the technology acceptance model (TAM) and theory of planned behavior (TPB) model integrated with new factors: perceived risk and knowledge of regulations. The study used random sampling of Amazon Mechanical Turk® (AMT) members using an AMT Human Intelligence Task (HIT) that included a link to an online cross-sectional large-scale survey to collect data. Data Analysis included descriptive statistics analysis and the SEM process. Besides developing and validating a model and determining influencing factors, attention was also on verifying the relationships between constructs. Study limitations and future research recommendations are also discussed. Results indicated the VMUTES model had a strong predictive power of sUAS use for data gathering with seven of the ten original hypotheses supported while having a good model fit. Four new hypotheses were also identified with three supported. Additionally, all VMUTES model factors except for facilitating conditions were determined to have either a direct or indirect effect on behavioral intention and/or actual behavior with the TAM and TPB related factors having the strongest effects. Practically, this study filled an aviation research knowledge gap for sUAS use for data gathering. It also provided a research model and identified influencing factors of individuals’ behavioral intentions related to sUAS for data gathering. Thus, the newly developed model incorporating new variables can be used for further sUAS research and can provide an adaptable model for aviation and other technology areas to predict and facilitate new technology implementation where current models fall short. Finally, this study explored new and verified previously existing demographic variables for individuals who use sUASs for data gathering