3D particle tracking velocimetry using dynamic discrete tomography

Particle tracking velocimetry in 3D is becoming an increasingly important imaging tool in the study of fluid dynamics, combustion as well as plasmas. We introduce a dynamic discrete tomography algorithm for reconstructing particle trajectories from projections. The algorithm is efficient for data from two projection directions and exact in the sense that it finds a solution consistent with the experimental data. Non-uniqueness of solutions can be detected and solutions can be tracked individually

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Airborne forward pointing UV Rayleigh lidar for remote clear air turbulence (CAT) detection: system design and performance

A high-performance airborne UV Rayleigh lidar system was developed within the European project DELICAT. With its forward-pointing architecture it aims at demonstrating a novel detection scheme for clear air turbulence (CAT) for an aeronautics safety application. Due to its occurrence in clear and clean air at high altitudes (aviation cruise flight level), this type of turbulence evades microwave radar techniques and in most cases coherent Doppler lidar techniques. The present lidar detection technique relies on air density fluctuations measurement and is thus independent of backscatter from hydrometeors and aerosol particles. The subtle air density fluctuations caused by the turbulent air flow demand exceptionally high stability of the setup and in particular of the detection system. This paper describes an airborne test system for the purpose of demonstrating this technology and turbulence detection method: a high-power UV Rayleigh lidar system is installed on a research aircraft in a forward-looking configuration for use in cruise flight altitudes. Flight test measurements demonstrate this unique lidar system being able to resolve air density fluctuations occurring in light-to-moderate CAT at 5 km or moderate CAT at 10 km distance. A scaling of the determined stability and noise characteristics shows that such performance is adequate for an application in commercial air transport.Comment: 17 pages, 19 figures. Pre-publish to Applied Optics (OSA

Precision Poultry Farming

This book presents the latest advances in applications of continuous, objective, and automated sensing technologies and computer tools for sustainable and efficient poultry production, and it offers solutions to the poultry industry to address challenges in terms of poultry management, the environment, nutrition, automation and robotics, health, welfare assessment, behavior monitoring, waste management, etc. The reader will find original research papers that address, on a global scale, the sustainability and efficiency of the poultry industry and explore the above-mentioned areas through applications of PPF solutions in poultry meat and egg productio

The Holy Grail: A road map for unlocking the climate record stored within Mars' polar layered deposits

In its polar layered deposits (PLD), Mars possesses a record of its recent climate, analogous to terrestrial ice sheets containing climate records on Earth. Each PLD is greater than 2 ​km thick and contains thousands of layers, each containing information on the climatic and atmospheric state during its deposition, creating a climate archive. With detailed measurements of layer composition, it may be possible to extract age, accumulation rates, atmospheric conditions, and surface activity at the time of deposition, among other important parameters; gaining the information would allow us to “read” the climate record. Because Mars has fewer complicating factors than Earth (e.g. oceans, biology, and human-modified climate), the planet offers a unique opportunity to study the history of a terrestrial planet’s climate, which in turn can teach us about our own planet and the thousands of terrestrial exoplanets waiting to be discovered. During a two-part workshop, the Keck Institute for Space Studies (KISS) hosted 38 Mars scientists and engineers who focused on determining the measurements needed to extract the climate record contained in the PLD. The group converged on four fundamental questions that must be answered with the goal of interpreting the climate record and finding its history based on the climate drivers. The group then proposed numerous measurements in order to answer these questions and detailed a sequence of missions and architecture to complete the measurements. In all, several missions are required, including an orbiter that can characterize the present climate and volatile reservoirs; a static reconnaissance lander capable of characterizing near surface atmospheric processes, annual accumulation, surface properties, and layer formation mechanism in the upper 50 ​cm of the PLD; a network of SmallSat landers focused on meteorology for ground truth of the low-altitude orbiter data; and finally, a second landed platform to access ~500 ​m of layers to measure layer variability through time. This mission architecture, with two landers, would meet the science goals and is designed to save costs compared to a single very capable landed mission. The rationale for this plan is presented below. In this paper we discuss numerous aspects, including our motivation, background of polar science, the climate science that drives polar layer formation, modeling of the atmosphere and climate to create hypotheses for what the layers mean, and terrestrial analogs to climatological studies. Finally, we present a list of measurements and missions required to answer the four major questions and read the climate record. 1. What are present and past fluxes of volatiles, dust, and other materials into and out of the polar regions? 2. How do orbital forcing and exchange with other reservoirs affect those fluxes? 3. What chemical and physical processes form and modify layers? 4. What is the timespan, completeness, and temporal resolution of the climate history recorded in the PLD

Sensors for Desert Surveillance

Various types of sensors-visible, passive night vision, infrared, synthetic aperture radar, etc can be used for desert surveillance. The surveillance capability of these sensors depends to a large extent, on various atmospheric effects, viz., absorption, scattering, aerosol, turbulence, and optical mirage. In this paper, effects of various atmospheric phenomena on the transmission of signals, merits and demerits of different means of surveillance under desert environmental conditions are discussed. Advanced surveillance techniques, ie, multisensor fusion, multi and hyperspectral imaging, having special significance for desert surveillance, have also been discussed

Early Forest Fire Detection and Verification using Optical Smoke, Gas and Microwave Sensors

AbstractThe research project “International Forest Fire Fighting” (iWBB) was funded by the Minister for Economic Affairs and Energy of the State of North Rhine-Westphalia, Germany. A group of companies, research institutes and universities have been working together to develop an integrated, but modular system. An integrated approach for early forest fire detection and suppression is based on an adequate combination of different detection systems depending on wildfire risk, the size of the area and human presence affiliated with an adequate logistical infrastructure, training by simulation, and innovative extinguishing technology. As in the case of wildfires large areas have to be monitored only remote sensing technologies (e.g. video based systems) are able to perform early detection adequately. To reduce false alarms a remote controlled unmanned aerial vehicle (UAV) equipped with gas sensors and a thermal camera flies to a potential fire to specify the origin of the reported cloud. The UAV can also be used as a scout for fire fighters. After successful fire extinction an unmanned blimp can be used as a fireguard to reduce the risk of re-ignition of the fire. As monitoring tools, a microwave radiometer detecting hot spots also at insufficient vision (due to smoke clouds and below the ground surface), gas and smoke sensors and a thermal camera are mounted on the blimp. The benefit of a blimp is a higher payload. This paper presents an investigation of an early forest fire detection system on the basis of indoor (performed in the fire lab of the University of Duisburg-Essen) and outdoor tests. A commercial highly sensitive aspirating smoke detector, two gas sensors (H2 and CXHX), a microwave radiometer and the detection algorithms are described. A general overview about the project and the carrier platforms is presented

Automatic Recognition of Light Microscope Pollen Images

This paper is a progress report on a project aimed at the realization of a low-cost, automatic, trainable system "AutoStage" for recognition and counting of pollen. Previous work on image feature selection and classification has been extended by design and integration of an XY stage to allow slides to be scanned, an auto focus system, and segmentation software. The results of a series of classification tests are reported, and verified by comparison with classification performance by expert palynologists. A number of technical issues are addressed, including pollen slide preparation and slide sampling protocols

Workshop on Advanced Technologies for Planetary Instruments, part 1

This meeting was conceived in response to new challenges facing NASA's robotic solar system exploration program. This volume contains papers presented at the Workshop on Advanced Technologies for Planetary Instruments on 28-30 Apr. 1993. This meeting was conceived in response to new challenges facing NASA's robotic solar system exploration program. Over the past several years, SDIO has sponsored a significant technology development program aimed, in part, at the production of instruments with these characteristics. This workshop provided an opportunity for specialists from the planetary science and DoD communities to establish contacts, to explore common technical ground in an open forum, and more specifically, to discuss the applicability of SDIO's technology base to planetary science instruments