UAS Flight Operations in Complex Terrain: Assessing the Agricultural Impact from Hurricane Maria in the Central Mountainous Region of Puerto Rico

Hurricane Maria struck Puerto Rico in September 2017 as a Category 4 storm causing major damage to infrastructure, agriculture and natural ecosystems, as well as the loss of many lives. Among the crops hardest hit was coffee, one of the most important crops in Puerto Rico. As a perennial system, coffee takes various production forms along a gradient from high shade/biodiversity coffee farms to low shade coffee monocultures and therefore offers an ideal means for the study of resistance and resilience of an agroecosystem to weather and climate disturbance. During the summer of 2018, 14 impacted farms across the production style gradient ranging in size from 10 to 100 acres were surveyed by a variety of UASs in order to investigate how a major weather disturbance affects production, biomass, biodiversity, and the recovery of each. All of the coffee farms were located within complex terrain and on the sides of mountains. This work addresses the flight challenges faced during the field campaign that include quickly changing terrain and tree canopies, limited launch and recovery areas, remote farms with limited access that was further exacerbated by storm damage, and mountain induced weather that produced complex flow patterns

Real-Time Urban Weather Observations for Urban Air Mobility

Cities of the future will have to overcome congestion, air pollution and increasing infrastructure cost while moving more people and goods smoothly, efficiently and in an eco-friendly manner. Urban air mobility (UAM) is expected to be an integral component of achieving this new type of city. This is a new environment for sustained aviation operations. The heterogeneity of the urban fabric and the roughness elements within it create a unique environment where flight conditions can change frequently across very short distances. UAM vehicles with their lower mass, more limited thrust and slower speeds are especially sensitive to these conditions. Since traditional aviation weather products for observations and forecasts at an airport on the outskirts of a metropolitan area do not translate well to the urban environment, weather data for low-altitude urban airspace is needed and will be particularly critical for unlocking the full potential of UAM. To help address this need, crowdsourced weather data from sources prevalent in urban areas offer the opportunity to create dense meteorological observation networks in support of UAM. This paper considers a variety of potential observational sources and proposes a cyber-physical system architecture, including an incentive-based crowdsensing application, which empowers UAM weather forecasting and operations

Development of a Telemetry System for a Meteorologically Instrumented Small Unmanned Aerial System

Small unmanned aerial systems (sUAS) are now being realized as an important instrument in atmospheric boundary layer (ABL) research where they fill an important gap between ground-based instruments and the altitudes that manned aircraft can safely operate at. They also provide a way to obtain high spatial resolution near-surface measurements between fixed meteorological infrastructure. While there have been several sUAS sensor suites developed for the measurement of scalar atmospheric parameters such as temperature, humidity, and pressure, only a small subset of these sensor suites are capable of measuring wind velocity. Most of these wind measurement solutions have been developed for fixed-wing unmanned aircraft. This work details the implementation of a telemetry system for a recently developed multirotor hosted meteorological instrumentation suite that measures both scalar atmospheric parameters and 3-dimensional wind components. Data is now successfully collected, transmitted and received in real time for the ground-based operations crew and scientific team

Development and verification of a three-dimensional wind measurement sensor hosted on a meteorologically instrumented small multirotor UAS

Small multirotor unmanned aerial systems (UAS) have great potential to effectively investigate the urban boundary layer. Their ability to launch and recover vertically in tight urban spaces, along with their ability to be precisely controlled, including hover, makes them an especially attractive investigation tool for obstacle laden environments. These aircraft characteristics are also conducive to obtaining measurements with both high spatial and temporal resolution. With the motivation to obtain high-resolution measurements, a small multirotor UAS was meteorologically instrumented with both thermodynamic and kinematic sensors. This work details the development and subsequent verification of two orthogonally mounted acoustic resonance ultrasonic anemometers that provide a 3 dimensional solution suitable for measurement of the mean wind and its fluctuating component (i.e. turbulence). Comparison of the geo and time-stamped wind speed and direction measurement was made against a surface mounted anemometer during both indoor and field testing. The system will be deployed in upcoming urban field campaigns in the summer of 2020 and beyond

Nocturnal Observations of Thermodynamic and Kinematic Properties in a Wind Turbine Array Boundary Layer Using an Instrumented Unmanned Aerial System

Observation, simulation, and modeling have shown that wind farms have an impact on the near-surface atmospheric boundary layer as turbulent wakes generated by the turbines enhance vertical mixing. These changes alter downstream atmospheric properties. With a large portion of wind farms hosted within an agricultural context, changes to the environment can potentially have secondary impacts such as to the productivity of crops. The authors, amongst others, have demonstrated changes to relative humidity and temperature within the wind turbine array boundary layer during daylight observations made by small unmanned aerial systems (sUAS). The obtainment of permission to fly at night and higher altitudes, along with the enhancement of the sUAS instrumentation suite with fast-response 3D sonic anemometers, enabled observations during overnight hours and at altitudes above the top turbine tip height. This talk details observed changes to thermodynamic and kinematic properties during an overnight field campaign undertaken during the summer of 2019 around a utility-scale wind turbine located within a variety of crops

Exploring the Impact of Early Exposure to Research on Dual Enrollment Students: A Qualitative Single-Case Study

Embry-Riddle Aeronautical University (ERAU) provides a concurrent enrollment model to high schools across the United States. The concurrent enrollment opportunity offers science, technology, engineering, and mathematics (STEM) college-credit coursework taught by college-credentialed instructors on the student’s high school campus. One faculty member transitioned to Embry-Riddle’s main residential campus following seven years of service with ERAU’s concurrent enrollment program. During his tenure with ERAU’s concurrent enrollment program, in addition to instructing a variety of concurrent enrollment courses, he maintained an active research agenda that involved concurrently enrolled students. His transition was preceded by the matriculation of a subset of these students to Embry-Riddle’s main campus. Each of these students immediately reengaged in undergraduate research with the faculty member while he continued to serve in a strong mentoring role. This presentation explores the affect this opportunity had on individual members of this tight-knit cohort as they progressed through their concurrent enrollment and undergraduate studies, participated in a long-standing mentoring relationship, and undertook their post-graduation decision-making. The research showcases project-based learning as a scaffolding technique for meaningful undergraduate research and how it may illuminate a pathway for students who do not initially see STEM as a viable option

Development of a Meteorologically Instrumented Small Transition Unmanned Aerial System For Urban Boundary Layer Investigations

It is estimated that more than 55% of the world’s population is currently living in urban areas and this number is expected to grow to 70% by 2050. The environment that houses this population is the urban boundary layer (UBL). The UBL is the portion of the atmospheric boundary layer whose characteristics are modified by the presence of a city and is regarded as one of the most complex and least understood environments. In order to investigate this region, an electric hybrid (transition) unmanned aerial system (UAS) was meteorologically instrumented. A hybrid UAS allows the meteorological sensor suite to be protected during vertical launch and recovery, allows for more deployment options in an urban environment, and capitalizes on the efficiency of forward flight. This work, under mentoring by Dr. Kevin Adkins, details the design, assembly and integration of the sensor suite that consists of a multi-hole pressure probe along with a temperature and humidity sensor. Each sensor’s data is time and geo-stamped and subsequently post-processed. The instrumented platform is planned to be fielded during the summer of 2020 and beyond

Real Time Data Downlink Device for Live Telemetry from Instrumented Vehicles

Real Time Data Downlink Device (RTDD) for Live Telemetry from Instrumented Vehicles Avinash Muthu Krishnan1, Marc D. Compere1, Kevin A. Adkins2 1 Department of Mechanical Engineering, Embry-Riddle Aeronautical University 2 Department of Aeronautical Science, Embry-Riddle Aeronautical University This paper presents a microcontroller and communications design that delivers real-time telemetry data over the cellular network from vehicles instrumented for scientific or engineering purposes. The Real Time Data Downlink (RTDD) device is being designed for atmospheric data collection on an aerial platform. While this application specifically pertains to the atmospheric sciences, the data collection technique is broadly applicable to ground, surface, or aerial platform data collection. The RTDD is implemented on four DJI Matrice-100 quadcopters that transmit real time position, wind speed, pressure, temperature and humidity over the cellular network. Each vehicle writes sensor data locally while simultaneously transmitting data samples to a data collection computer for real time experiment monitoring. The data collection computer runs an open-sourced software called the Mobility Virtual Environment (MoVE). MoVE aggregates all incoming data streams from each vehicle to provide a comprehensive picture of the scenario with a live 2D map display of all vehicles and a browser-based table to present the data. The RTDD provides real time data thus ensuring complete mission execution and confirmation of sensor performance. Therefore, the RTDD is a critical component of the instrumented aircraft and an overall successful multi-vehicle data collection effort

Low-cost Sensors on Unmanned Aerial Vehicles: an Advancement in Air Quality Measurement

With the rapid industrialization and the current status of climate change, air pollution has become a global concern. However, detecting atmospheric pollutants is costly, time-consuming, and cumbersome. Currently, the Environmental Protection Agency (US EPA) utilizes filter-based techniques in their federal reference and federal equivalent methods (FRM and FEM, respectively) to measure ground-based particulate matter (PM) levels in the atmosphere. Recently, the development of low-cost sensors has helped in combatting the high cost associated with acquiring these measurements. These sensors allow for PM concentrations to be measured at high resolutions. Due to their surface mounted nature, the EPA’s methods are limited in measuring the concentrations of PM at the ground-level. Hence, they lack the ability of determining the concentrations at various altitudes, which is important in characterizing the origin and the formation pathway of such pollutants. To address these shortcomings, we propose placing multiple low-cost sensors on Unmanned Aerial Vehicles (UAVs) to measure the concentrations of PM in Daytona Beach, FL. Sampling will be conducted seasonally, and the PM concentrations will be compared to their counterpart observations obtained using the EPA’s methods. The findings of this study should aid in the development of low-cost air pollution sensors that can be hosted on UAVs. This work promises to be advantageous in detecting air pollutants in both congested and remote areas

New Air Quality Measurement Method: Low-Cost Sensors on UAV’s

With the rapid industrialization and the current status of climate change, air pollution has become a global concern. However, detecting atmospheric pollutants is costly, time-consuming, and cumbersome. Currently, the Environmental Protection Agency (US EPA) utilizes filter-based techniques in their federal reference and federal equivalent methods (FRM and FEM, respectively) to measure ground-based particulate matter (PM) levels in the atmosphere. Recently, the development of low-cost sensors has helped in combatting the high cost associated with acquiring these measurements. These sensors allow for PM concentrations to be measured at high resolutions. Due to their surface mounted nature, the EPA’s methods are limited in measuring the concentrations of PM at the ground-level. Hence, they lack the ability of determining the concentrations at various altitudes, which is important in characterizing the origin and the formation pathway of such pollutants. To address these shortcomings, we propose placing multiple low-cost sensors on Unmanned Aerial Vehicles (UAVs) to measure the concentrations of PM in Daytona Beach, FL. Sampling will be conducted seasonally, and the PM concentrations will be compared to their counterpart observations obtained using the EPA’s methods. The findings of this study should aid in the development of low-cost air pollution sensors that can be hosted on UAVs. This work promises to be advantageous in detecting air pollutants in both congested and remote areas