Multidisciplinary design and flight testing of a remote gas/particle airborne sensor system

The main objective of this paper is to describe the development of a remote sensing airborne air sampling system for Unmanned Aerial Systems (UAS) and provide the capability for the detection of particle and gas concentrations in real time over remote locations. The design of the air sampling methodology started by defining system architecture, and then by selecting and integrating each subsystem. A multifunctional air sampling instrument, with capability for simultaneous measurement of particle and gas concentrations was modified and integrated with ARCAA’s Flamingo UAS platform and communications protocols. As result of the integration process, a system capable of both real time geo-location monitoring and indexed-link sampling was obtained. Wind tunnel tests were conducted in order to evaluate the performance of the air sampling instrument in controlled nonstationary conditions at the typical operational velocities of the UAS platform. Once the remote fully operative air sampling system was obtained, the problem of mission design was analyzed through the simulation of different scenarios. Furthermore, flight tests of the complete air sampling system were then conducted to check the dynamic characteristics of the UAS with the air sampling system and to prove its capability to perform an air sampling mission following a specific flight path

Review article: The use of remotely piloted aircraft systems (RPAS) for natural hazards monitoring and management

The number of scientific studies that consider possible applications of Remotely Piloted Aircraft Systems (RPAS) for the management of natural hazards effects and the identification of occurred damages are strongly increased in last decade. Nowadays, in the scientific community, the use of these systems is not a novelty, but a deeper analysis of literature shows a lack of codified complex methodologies that can be used not only for scientific experiments but also for normal codified emergency operations. RPAS can acquire on-demand ultra-high resolution images that can be used for the identification of active processes like landslides or volcanic activities but also for the definition of effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologiesdeveloped for the study and monitoring of natural hazards

Review article: The use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

The number of scientific studies that consider possible applications of remotely piloted aircraft systems (RPASs) for the management of natural hazards effects and the identification of occurred damages strongly increased in the last decade. Nowadays, in the scientific community, the use of these systems is not a novelty, but a deeper analysis of the literature shows a lack of codified complex methodologies that can be used not only for scientific experiments but also for normal codified emergency operations. RPASs can acquire on-demand ultra-high-resolution images that can be used for the identification of active processes such as landslides or volcanic activities but can also define the effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologies developed for the study and monitoring of natural hazard

Numerical fluid dynamics simulation for drones’ chemical detection

The risk associated with chemical, biological, radiological, nuclear, and explosive (CBRNe) threats in the last two decades has grown as a result of easier access to hazardous materials and agents, potentially increasing the chance for dangerous events. Consequently, early detection of a threat following a CBRNe event is a mandatory requirement for the safety and security of human operators involved in the management of the emergency. Drones are nowadays one of the most advanced and versatile tools available, and they have proven to be successfully used in many different application fields. The use of drones equipped with inexpensive and selective detectors could be both a solution to improve the early detection of threats and, at the same time, a solution for human operators to prevent dangerous situations. To maximize the drone’s capability of detecting dangerous volatile substances, fluid dynamics numerical simulations may be used to understand the optimal configuration of the detectors positioned on the drone. This study serves as a first step to investigate how the fluid dynamics of the drone propeller flow and the different sensors position on-board could affect the conditioning and acquisition of data. The first consequence of this approach may lead to optimizing the position of the detectors on the drone based not only on the specific technology of the sensor, but also on the type of chemical agent dispersed in the environment, eventually allowing to define a technological solution to enhance the detection process and ensure the safety and security of first responders

Smelling Nano Aerial Vehicle for Gas Source Localization and Mapping

This paper describes the development and validation of the currently smallest aerial platform with olfaction capabilities. The developed Smelling Nano Aerial Vehicle (SNAV) is based on a lightweight commercial nano-quadcopter (27 g) equipped with a custom gas sensing board that can host up to two in situ metal oxide semiconductor (MOX) gas sensors. Due to its small form-factor, the SNAV is not a hazard for humans, enabling its use in public areas or inside buildings. It can autonomously carry out gas sensing missions of hazardous environments inaccessible to terrestrial robots and bigger drones, for example searching for victims and hazardous gas leaks inside pockets that form within the wreckage of collapsed buildings in the aftermath of an earthquake or explosion. The first contribution of this work is assessing the impact of the nano-propellers on the MOX sensor signals at different distances to a gas source. A second contribution is adapting the 'bout' detection algorithm, proposed by Schmuker et al. (2016) to extract specific features from the derivative of the MOX sensor response, for real-time operation. The third and main contribution is the experimental validation of the SNAV for gas source localization (GSL) and mapping in a large indoor environment (160 m²) with a gas source placed in challenging positions for the drone, for example hidden in the ceiling of the room or inside a power outlet box. Two GSL strategies are compared, one based on the instantaneous gas sensor response and the other one based on the bout frequency. From the measurements collected (in motion) along a predefined sweeping path we built (in less than 3 min) a 3D map of the gas distribution and identified the most likely source location. Using the bout frequency yielded on average a higher localization accuracy than using the instantaneous gas sensor response (1.38 m versus 2.05 m error), however accurate tuning of an additional parameter (the noise threshold) is required in the former case. The main conclusion of this paper is that a nano-drone has the potential to perform gas sensing tasks in complex environments

Using Drones in Disaster Areas: Perspectives of Disaster Responders in North Carolina, Virginia and Maryland

Drones are pilotless aircraft and are more formally known as either unmanned aerial vehicles (UAVs) or unmanned aircraft systems (UAS). Drones, as they were referred to in this study, have the capability of being remotely controlled or flying autonomously through software-controlled flight plans that are embedded as part of their navigation systems. The navigation systems include onboard sensors and GPS that provide options to expand the range of responses in dealing with emergencies. Although, drones have been more widely used for military operations, they are increasingly being used as part of emergency response and public safety operations. This aspect of emerging drone use in North Carolina, Virginia and Maryland is the overarching purpose of this study. This study explores factors that influence the effectiveness and efficiency of using drones for disaster preparedness and response operations including assessment of damage following disasters, re-establishing critical communication channels, rescue and evacuation of victims, and the delivery of much needed supplies. It also analyzes specific disasters involving flooding due to hurricanes, and damage as a result of tornadoes and brush fires in North Carolina, Virginia, and Maryland. Due to the impact of climate change, extreme temperatures, rising sea levels, extreme hurricanes and decreased water resources, the fact that these three states have been affected by billion-dollar level disaster damage is cause for concern

UAVs for the Environmental Sciences

This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application