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.

Community participation in the development of digital radio : the Australian experience

The participation of the community broadcasting sector in the development of digital radio provides a potentially valuable opportunity for non-market, end user-driven experimentation in the development of these new services in Australia. However this development path is constrained by various factors, some of which are specific to the community broadcasting sector and others that are generic to the broader media and communications policy, industrial and technological context. This paper filters recent developments in digital radio policy and implementation through the perspectives of community radio stakeholders, obtained through interviews, to describe and analyse these constraints. The early stage of digital community radio presented here is intended as a baseline for tracking the development of the sector as digital radio broadcasting develops. We also draw upon insights from scholarly debates about citizens media and participatory culture to identify and discuss two sets of opportunities for social benefit that are enabled by the inclusion of community radio in digital radio service development. The first arises from community broadcasting’s involvement in the propagation of the multi-literacies that drive new digital economies, not only through formal and informal multi- and trans-media training, but also in the ‘co-creative’ forms of collaborative and participatory media production that are fostered in the sector. The second arises from the fact that community radio is uniquely placed — indeed charged with the responsibility — to facilitate social participation in the design and operation of media institutions themselves, not just their service outputs.

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.

Spectrum sensing, detection and optimisation in cognitive radio for non-stationary primary user signals

Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.

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.

Imaging affect : abstraction and the echo of the unknowable

As an artist my primary interest is in the abstract, that is in images of the imageless. I am curious about the emergence of pictorial significance and content from this unknowable space. To speak of the significance of an imageless image is also to speak of its affect. I aim to explore this both theoretically and practically. Theoretically I will explore affect through the late work of Lyotard and his notion of the affect-phrase. This is an under-examined aspect of Lyotard and demarcates a valuable way to look at the origins, impact and ramifications of affect for art. Practically I will apply these understandings to the development of my own creative work which includes both painting and digital work. My studio practice moves towards exploring the unfamiliar through the powerful and restless silence of affect.In this intense space each work or body of work 'leaks' into the next occasioning a sense of borderlessness, or of uncertainty. This interpenetration and co-mingling of conceptual and material terrains combines to present temporal and spatial slippages evident within the works themselves and their making, but it is also evident in bodies of work across the chronology of their making. Through a mapping of my own painting and digital arts practice and the utilisation of Lyotard’s notion of the affect -phrase I aim to describe the action of this ‘charged emptiness’ on creativity and explore and explain its significance on that we call image and its animation of what we call critical discourse.