Evaluating unmanned aircraft systems for deployment in plant biosecurity

This report provides a qualitative evaluation of Unmanned Aircraft Systems (UAS) and on-board sensor technology for use in plant biosecurity in the Australian context. The more general term UAS describes both the Unmanned Aerial Vehicle (UAV) and all supporting components required to operate it. This may include a ground station, operator or pilot, and a launch and recovery device for example. The focus is to identify how and under what circumstances UAS may be useful for plant biosecurity. This can be used to help guide future decisions regarding investment in UAS for plant biosecurity.

Strategies for three dimensional deployment of tethered satellites

Tethered satellites deployed from the Space Shuttle have been proposed for diverse applications. A funda- mental issue in the utilization of tethers is quick deployment and retrieval of the attached payload. Inordinate librations of the tether during deployment and retrieval is undesirable. The structural damping present in the system is too low to contain the librations. Rupp [1] proposed to control the tether reel located in the parent spacecraft to alter the tension in the tether, which in turn changes the stiffness and the damping of the system. Baker[2] applied the tension control law to a model which included out of plane motion. Modi et al.[3] proposed a control law that included nonlinear feedback of the out-of plane tether angular rate. More recently, nonlinear feedback control laws based on Liapunov functions have been proposed. Two control laws are derived in [4]. The first is based on partial decomposition of the equations of motion and utilization of a two dimensional control law developed in [5]. The other is based on a Liapunov function that takes into consideration out-of-plane motion. It is shown[4] that the control laws are effective when used in conjunction with out-of-plane thrusting. Fujii et al.,[6] used the mission function control approach to study the control law including aerodynamic drag effect explicitly into the control algorithm.

Supporting the development and deployment of sustainable energy technologies through targeted scientific training

Sustainable energy technologies rely heavily on advanced materials and modern engineering controls. These promising new technologies cannot be reliably deployed without ensuring that there is a sufficient “capacity,” i.e., trained technical personnel with the expertise to implement, monitor, and maintain the energy infrastructure. This same capacity is critical to the local development of new technologies, especially those that respond directly to regional priorities, strengths, and needs. One way to build capacity is through targeted programs that integrate the training and development of locals at an advanced technical level. In practical terms, these programs usually produce a small number of highly educated individuals with skills in science and engineering. The goal of Part VI of this book is to highlight contributing factors in successfully operating capacity building programs.

Comparative performance of Corymbia hybrids and parental species in subtropical Queensland and implications for breeding and deployment.

Eighty six full-sib Corymbia F1 hybrid families (crosses between C. torelliana and four spotted gum taxa: C. citriodora subsp. variegata, C. citriodora subsp. citriodora, C. henryi and C. maculata), were planted in six trials across six disparate sites in south-eastern Queensland to evaluate their productivity and determine their potential utility for plantation forestry. In each trial, the best-growing 20% of hybrid families grew significantly faster (P=0.05) than open-pollinated seedlots of the parent species Corymbia citriodora subsp. variegata, ranging from 107% to 181% and 127% to 287% of the height and diameter respectively. Relative performance of hybrid families growing on more than one site displayed consistency in ranking for growth across sites and analysis showed low genotype-by-environment interaction. Heritability estimates based on female and male parents across two sites at age six years for height and diameter at breast height, were high (0.62±0.28 to 0.64±0.35 and 0.31±0.21 to 0.69±0.37 respectively), and low to moderate (0.03±0.04 to 0.33±0.22) for stem straightness, branch size, incidence of ramicorns, and frost and disease resistance traits at ages one to three years. The proportion of dominance variance for height and diameter had reduced to zero by age six years. Based on these promising results, further breeding and pilot-scale family forestry and clonal forestry deployment is being undertaken. These results have also provided insights regarding the choice of a future hybrid breeding strategy.

Deployment of Elite Tropical and Subtropical Hardwoods

Commercialisation agreements supporting plantation development, carbon sequestration, climate change of hardwood species in Queensland.

Classifying genotype by environment interactions for targeted germplasm deployment with a focus on Eucalyptus

A novel methodology for describing genotype by environment interactions estimated from multi-environment field trials is described and an empirical example using an extensive trial network of eucalypts is presented. The network of experiments containing 65 eucalypts was established in 38 replicated field trials across the tropics and subtropics of eastern Australia, with a selection of well-tested species used to provide a more detailed examination of productivity differentials across environmental gradients. By focusing on changes in species’ productivity across environmental gradients, the results are applicable for all species established across the range of environments evaluated in the trial network and simultaneously classify species and environments so that results may be applied across the landscape. The methodology developed was able to explain most (93 %) of the variation in the selected species relative changes in productivity across the various environmental variables examined. Responses were primarily regulated by changes in variables related to water availability and secondarily by temperature related variables. Clustering and ordination can identify groups of species with similar physiological responses to environment and may also guide the parameterisation and calibration of process based models of plant growth. Ordination was particularly useful in the identification of species with distinct environmental response patterns that would be useful as probes for extracting more information from future trials.

Sensor network deployment for agronomical data gathering in semi-arid regions

We share our experience in planning, designing and deploying a wireless sensor network of one square kilometre area. Environmental data such as soil moisture, temperature, barometric pressure, and relative humidity are collected in this area situated in the semi-arid region of Karnataka, India. It is a hope that information derived from this data will benefit the marginal farmer towards improving his farming practices. Soon after establishing the need for such a project, we begin by showing the big picture of such a data gathering network, the software architecture we have used, the range measurements needed for determining the sensor density, and the packaging issues that seem to play a crucial role in field deployments. Our field deployment experiences include designing with intermittent grid power, enhancing software tools to aid quicker and effective deployment, and flash memory corruption. The first results on data gathering look encouraging.

Building Information Modelling – Experts´ Views on Standardisation and Industry Deployment

The goal of the single building information model has existed for at least thirty years and various standards have been published leading up to the ten-year development of the Industry Foundation Classes. These have been initiatives from researchers, software developers and standards committees. Now large property owners are becoming aware of the benefits of moving IT tools from specific applications towards more comprehensive solutions. This study addresses the state of Building Information Models and the conditions necessary for them to become more widely used. It is a qualitative study based on information from a number of international experts and has asked a series of questions about the feasibility of BIMs, the conditions necessary for their success, and the role of standards with particular reference to the IFCs. Some key statements were distilled from the diverse answers received and indicate that BIM solutions appear too complex for many and may need to be applied in limited areas initially. Standards are generally supported but not applied rigorously and a range of these are relevant to BIM. Benefits will depend upon the building procurement methods used and there should be special roles within the project team to manage information. Case studies are starting to appear and these could be used for publicity. The IFCs are rather oversold and their complexities should be hidden within simple-to-use software. Inevitably major questions remain and property owners may be the key to answering some of these. A framework for presenting standards, backed up by case studies of successful projects, is the solution proposed to provide better information on where particular BIM standards and solutions should be applied in building projects.

Lessons from the Sparse Sensor Network Deployment in Rural India

We discuss the key issues in the deployment of sparse sensor networks. The network monitors several environment parameters and is deployed in a semi-arid region for the benefit of small and marginal farmers. We begin by discussing the problems of an existing unreliable 1 sq km sparse network deployed in a village. The proposed solutions are implemented in a new cluster. The new cluster is a reliable 5 sq km network. Our contributions are two fold. Firstly, we describe a. novel methodology to deploy a sparse reliable data gathering sensor network and evaluate the ``safe distance'' or ``reliable'' distance between nodes using propagation models. Secondly, we address the problem of transporting data from rural aggregation servers to urban data centres. This paper tracks our steps in deploying a sensor network in a village,in India, trying to provide better diagnosis for better crop management. Keywords - Rural, Agriculture, CTRS, Sparse.

Application of an evolutionary fuzzy system for the estimation of workforce deployment and cross-training in an assembly environment

Owing to the increased customer demands for make-to-order products and smaller product life-cycles, today assembly lines are designed to ensure a quick switch-over from one product model to another for companies' survival in market place. The complexity associated with the decisions pertaining to the type of training and number of workers and their exposition to the different tasks especially in the current era of customized production is a serious problem that the managers and the HRD gurus are facing in industry. This paper aims to determine the amount of cross-training and dynamic deployment policy caused by workforce flexibility for a make-to-order assembly. The aforementioned issues have been dealt with by adopting the concept of evolutionary fuzzy system because of the linguistic nature of the attributes associated with product variety and task complexity. A fuzzy system-based methodology is proposed to determine the amount of cross-training and dynamic deployment policy. The proposed methodology is tested on 10 sample products of varying complexities and the results obtained are in line with the conclusions drawn by previous researchers.

Optimizing deployment of multiple decoys to enhance ship survivability

In this paper we model a scenario where a ship uses decoys to evade a hostile torpedo. We address the problem of enhancing ship survivability against enemy torpedoes by using single and multiple decoy deployments. We incorporate deterministic ship maneuvers and realistic constraints on turn rates, field of view, etc in the model. We formulate the objective function to quantify and maximize the survivability of the ship in terms of maximizing the intercept time. We introduce the concept of optimal deployment regions, same side deployment, and zig-zag deployment strategies. Finally, we present simulation results.

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.

Smartconnect: a system for the design and deployment of wireless sensor networks

We have developed SmartConnect, a tool that addresses the growing need for the design and deployment of multihop wireless relay networks for connecting sensors to a control center. Given the locations of the sensors, the traffic that each sensor generates, the quality of service (QoS) requirements, and the potential locations at which relays can be placed, SmartConnect helps design and deploy a low-cost wireless multihop relay network. SmartConnect adopts a field interactive, iterative approach, with model based network design, field evaluation and relay augmentation performed iteratively until the desired QoS is met. The design process is based on approximate combinatorial optimization algorithms. In the paper, we provide the design choices made in SmartConnect and describe the experimental work that led to these choices. Finally, we provide results from some experimental deployments.