Compensation of unmodeled aircraft dynamics in airborne inspection of linear infrastructure assets

Fixed-wing aircraft equipped with downward pointing cameras and/or LiDAR can be used for inspecting approximately piecewise linear assets such as oil-gas pipelines, roads and power-lines. Automatic control of such aircraft is important from a productivity and safety point of view (long periods of precision manual flight at low-altitude is not considered reasonable from a safety perspective). This paper investigates the effect of any unwanted coupling between guidance and autopilot loops (typically caused by unmodeled delays in the aircraft’s response), and the specific impact of any unwanted dynamics on the performance of aircraft undertaking inspection of piecewise linear corridor assets (such as powerlines). Simulation studies and experimental flight tests are used to demonstrate the benefits of a simple compensator in mitigating the unwanted lateral oscillatory behaviour (or coupling) that is caused by unmodeled time constants in the aircraft dynamics.

Detection versus false alarm characterisation of a vision-based airborne dim-target collision detection system

This paper presents a preliminary flight test based detection range versus false alarm performance characterisation of a morphological-hidden Markov model filtering approach to vision-based airborne dim-target collision detection. On the basis of compelling in-flight collision scenario data, we calculate system operating characteristic (SOC) curves that concisely illustrate the detection range versus false alarm rate performance design trade-offs. These preliminary SOC curves provide a more complete dim-target detection performance description than previous studies (due to the experimental difficulties involved, previous studies have been limited to very short flight data sample sets and hence have not been able to quantify false alarm behaviour). The preliminary investigation here is based on data collected from 4 controlled collision encounters and supporting non-target flight data. This study suggests head-on detection ranges of approximately 2.22 km under blue sky background conditions (1.26 km in cluttered background conditions), whilst experiencing false alarms at a rate less than 1.7 false alarms/hour (ie. less than once every 36 minutes). Further data collection is currently in progress.

Room ventilation and the risk of airborne infection transmission in three health care settings within a large teaching hospital

Background: Room ventilation is a key determinant of airborne disease transmission. Despite this, ventilation guidelines in hospitals are not founded on robust scientific evidence related to prevention of airborne transmission. Methods: We sought to assess the effect of ventilation rates on influenza, tuberculosis (TB) and rhinovirus infection risk within three distinct rooms in a major urban hospital; a Lung Function Laboratory, Emergency Department (ED) Negative-pressure Isolation Room and an Outpatient Consultation Room were investigated. Air exchange rate measurements were performed in each room using CO2 as a tracer. Gammaitoni and Nucci’s model was employed to estimate infection risk. Results: Current outdoor air exchange rates in the Lung Function Laboratory and ED Isolation Room limited infection risks to between 0.1 and 3.6%. Influenza risk for individuals entering an Outpatient Consultation Room after an infectious individual departed ranged from 3.6 to 20.7%, depending on the duration for which each person occupied the room. Conclusions: Given the absence of definitive ventilation guidelines for hospitals, air exchange measurements combined with modelling afford a useful means of assessing, on a case-by-case basis, the suitability of room ventilation at preventing airborne disease transmission.

Demonstration of closed-­loop airborne sense-­and-­avoid using machine vision

This paper describes a vision-based airborne collision avoidance system developed by the Australian Research Centre for Aerospace Automation (ARCAA) under its Dynamic Sense-and-Act (DSA) program. We outline the system architecture and the flight testing undertaken to validate the system performance under realistic collision course scenarios. The proposed system could be implemented in either manned or unmanned aircraft, and represents a step forward in the development of a “sense-and-avoid” capability equivalent to human “see-and-avoid”.

Flying Spore Trap Airborne Based Surveillance : towards a Biosecure Australia

The main limitations with existing fungal spore traps are that they are stationary and cannot be used in inaccessible or remote areas of Australia. This may result in delayed assessment, possible spread of harmful crop infestations and loss of crop yield and productivity. Fitted with the developed smart spore trap the UAV can fly, detect and monitor spores of plant pathogens in areas which previously were almost impossible to monitor. The technology will allow for earlier detection of emergency plant pests (EPPs) incursions by providing efficient and effective airborne surveillance, helping to protect Australia’s crops, pastures and the environment. The project is led by the Cooperative Research Centre for National Plant Biosecurity, with ARCAA/ QUT, CSIRO and the Queensland Government also providing resources. The prototype airplane was exhibited at the Innovation in Australia event December 7.

The risk of airborne influenza transmission in passenger cars

Travel in passenger cars is a ubiquitous aspect of the daily activities of many people. During the 2009 influenza A (H1N1) pandemic a case of probable transmission during car travel was reported in Australia, to which spread via the airborne route may have contributed. However, there are no data to indicate the likely risks of such events, and how they may vary and be mitigated. To address this knowledge gap, we estimated the risk of airborne influenza transmission in two cars (1989 model and 2005 model) by employing ventilation measurements and a variation of the Wells-Riley model. Results suggested that infection risk can be reduced by not recirculating air; however, estimated risk ranged from 59 to 99.9% for a 90 min trip when air was recirculated in the newer vehicle. These results have implications for interrupting in-car transmission of other illnesses spread by the airborne route.

Vacuum cleaner emissions as a source of indoor exposure to airborne particles and bacteria

Vacuuming can be a source of indoor exposure to biological and non-biological aerosols, although there is little data that describes the magnitude of emissions from the vacuum cleaner itself. We therefore sought to quantify emission rates of particles and bacteria from a large group of vacuum cleaners and investigate their potential determinants, including temperature, dust bags, exhaust filters, price and age. Emissions of particles between 0.009 and 20 µm and bacteria were measured from 21 vacuums. Ultrafine (<100 nm) particle emission rates ranged from 4.0 × 10^6 to 1.1 × 10^11 particles min-1. Emission of 0.54 to 20 µm particles ranged from 4.0 × 10^4 to 1.2 × 10^9 particles min-1. PM2.5 emissions were between 2.4 × 10-1 and 5.4 × 10^3 µg min-1. Bacteria emissions ranged from 0 to 7.4 × 10^5 bacteria min-1 and were poorly correlated with dust bag bacteria content and particle emissions. Large variability in emission of all parameters was observed across the 21 vacuums we assessed, which was largely not attributable to the range of determinant factors we assessed. Vacuum cleaner emissions contribute to indoor exposure to non-biological and biological aerosols when vacuuming, and this may vary markedly depending on the vacuum used.

Fusion of morphological images for airborne target detection

Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

Airborne particle concentrations at schools measured at different spatial scales

Potential adverse effects on children health may result from school exposure to airborne particles. To address this issue, measurements in terms of particle number concentration, particle size distribution and black carbon (BC) concentrations were performed in three school buildings in Cassino (Italy) and its suburbs, outside and inside of the classrooms during normal occupancy and use. Additional time resolved information was gathered on ventilation condition, classroom activity, and traffic count data around the schools were obtained using a video camera. Across the three investigated school buildings, the outdoor and indoor particle number concentration monitored down to 4 nm and up to 3 m ranged from 2.8×104 part cm-3 to 4.7×104 part cm-3 and from 2.0×104 part cm-3 to 3.5×104 part cm-3, respectively. The total particle concentrations were usually higher outdoors than indoors, because no indoor sources were detected. I/O measured was less than 1 (varying in a relatively narrow range from 0.63 to 0.74), however one school exhibited indoor concentrations higher than outdoor during the morning rush hours. Particle size distribution at the outdoor site showed high particle concentrations in different size ranges, varying during the day; in relation to the starting and finishing of school time two modes were found. BC concentrations were 5 times higher at the urban school compared with the suburban and suburban-to-urban differences were larger than the relative differences of ultrafine particle concentrations.

Airborne concentration of Volatile Organic Compounds in school environment in Brisbane

Traffic emissions are considered as a major source of pollutants, particularly ultrafine particles, in the urban environment. There is an increased concern about airborne particles not only because of their environmental effects but also due to their potential adverse health effects on humans. There have been a number of studies related to the number concentration and size distribution of these particles but studies on the chemical composition of aerosols, especially in the school environment, are very limited. Mejia et. al (2011) reviewed studies on the exposure to and impact of air pollutants on school children and found that there were only a handful of studies on this topic. Therefore, the main focus of this research is on an analysis of the chemical composition of airborne particles, as well as source apportionment and the quantification of ambient concentrations of organic pollutants in the vicinity of schools, as a part of “Ultrafine Particles from Traffic Emissions on Children’s Health” (UPTECH) project. The aim of the present study was to find out the concentrations of different Volatile Organic Compounds (VOCs) in both outdoor and indoor locations from six different schools in Brisbane.

Exposure to airborne fungi and bacteria in Brisbane houses after the 2011 flood

A series of flooding events occurred in Queensland, Australia during December 2010 and January 2011. The state’s capital city of Brisbane experienced major flooding in January 2011, when the Brisbane River broke its bank and inundated low lying areas.

Preliminary results on the chemical composition of outdoor airborne particles at urban schools and possible implications for the air quality in classrooms

Vehicle emissions are a significant source of fine particles (Dp < 2.5 µm) in an urban environment. These fine particles have been shown to have detrimental health effects, with children thought to be more susceptible. Vehicle emissions are mainly carbonaceous in nature, and carbonaceous aerosols can be defined as either elemental carbon (EC) or organic carbon (OC). EC is a soot-like material emitted from primary sources while OC fraction is a complex mixture of hundreds of organic compounds from either primary or secondary sources (Cao et al., 2006). Therefore the ratio of OC/EC can aid in the identification of source. The purpose of this paper is to use the concentration of OC and EC in fine particles to determine the levels of vehicle emissions in schools. It is expected that this will improve the understanding of the potential exposure of children in a school environment to vehicle emissions.

Characterization of sky-region morphological-temporal airborne collision detection

Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

Airborne collision scenario flight tests : impact of angle measurement errors on reactive vision-based avoidance control

The future emergence of many types of airborne vehicles and unpiloted aircraft in the national airspace means collision avoidance is of primary concern in an uncooperative airspace environment. The ability to replicate a pilot’s see and avoid capability using cameras coupled with vision based avoidance control is an important part of an overall collision avoidance strategy. But unfortunately without range collision avoidance has no direct way to guarantee a level of safety. Collision scenario flight tests with two aircraft and a monocular camera threat detection and tracking system were used to study the accuracy of image-derived angle measurements. The effect of image-derived angle errors on reactive vision-based avoidance performance was then studied by simulation. The results show that whilst large angle measurement errors can significantly affect minimum ranging characteristics across a variety of initial conditions and closing speeds, the minimum range is always bounded and a collision never occurs.