The Application of wireless LANS in mine automation

The objective of this paper is to provide an overview of mine automation applications, developed at the Queensland Centre for Advanced Technology (QCAT), which make use of IEEE 802.11b wireless local area networks (WLANs). The paper has been prepared for a 2002 conference entitled "Creating the Virtual Enterprise - Leveraging wireless technology within existing business models for corporate advantage". Descriptions of the WLAN components have been omitted here as such details are presented in the accompanying papers. The structure of the paper is as follows. Application overviews are provided in Sections 2 to 7. Some pertinent strengths and weaknesses are summarised in Section 8. Please refer to http://www.mining-automation.com/ or contact the authors for further information.

An initial technology roadmap for home automation : home and personal life management

Home Automation (HA) has emerged as a prominent ¯eld for researchers and in- vestors confronting the challenge of penetrating the average home user market with products and services emerging from technology based vision. In spite of many technology contri- butions, there is a latent demand for a®ordable and pragmatic assistive technologies for pro-active handling of complex lifestyle related problems faced by home users. This study has pioneered to develop an Initial Technology Roadmap for HA (ITRHA) that formulates a need based vision of 10-15 years, identifying market, product and technology investment opportunities, focusing on those aspects of HA contributing to e±cient management of home and personal life. The concept of Family Life Cycle is developed to understand the temporal needs of family. In order to formally describe a coherent set of family processes, their relationships, and interaction with external elements, a reference model named Fam- ily System is established that identi¯es External Entities, 7 major Family Processes, and 7 subsystems-Finance, Meals, Health, Education, Career, Housing, and Socialisation. Anal- ysis of these subsystems reveals Soft, Hard and Hybrid processes. Rectifying the lack of formal methods for eliciting future user requirements and reassessing evolving market needs, this study has developed a novel method called Requirement Elicitation of Future Users by Systems Scenario (REFUSS), integrating process modelling, and scenario technique within the framework of roadmapping. The REFUSS is used to systematically derive process au- tomation needs relating the process knowledge to future user characteristics identi¯ed from scenarios created to visualise di®erent futures with richly detailed information on lifestyle trends thus enabling learning about the future requirements. Revealing an addressable market size estimate of billions of dollars per annum this research has developed innovative ideas on software based products including Document Management Systems facilitating automated collection, easy retrieval of all documents, In- formation Management System automating information services and Ubiquitous Intelligent System empowering the highly mobile home users with ambient intelligence. Other product ideas include robotic devices of versatile Kitchen Hand and Cleaner Arm that can be time saving. Materialisation of these products require technology investment initiating further research in areas of data extraction, and information integration as well as manipulation and perception, sensor actuator system, tactile sensing, odour detection, and robotic controller. This study recommends new policies on electronic data delivery from service providers as well as new standards on XML based document structure and format.

Modelling and execution of asset management process via workflow automation

An Asset Management (AM) life-cycle constitutes a set of processes that align with the development, operation and maintenance of assets, in order to meet the desired requirements and objectives of the stake holders of the business. The scope of AM is often broad within an organization due to the interactions between its internal elements such as human resources, finance, technology, engineering operation, information technology and management, as well as external elements such as governance and environment. Due to the complexity of the AM processes, it has been proposed that in order to optimize asset management activities, process modelling initiatives should be adopted. Although organisations adopt AM principles and carry out AM initiatives, most do not document or model their AM processes, let alone enacting their processes (semi-) automatically using a computer-supported system. There is currently a lack of knowledge describing how to model AM processes through a methodical and suitable manner so that the processes are streamlines and optimized and are ready for deployment in a computerised way. This research aims to overcome this deficiency by developing an approach that will aid organisations in constructing AM process models quickly and systematically whilst using the most appropriate techniques, such as workflow technology. Currently, there is a wealth of information within the individual domains of AM and workflow. Both fields are gaining significant popularity in many industries thus fuelling the need for research in exploring the possible benefits of their cross-disciplinary applications. This research is thus inspired to investigate these two domains to exploit the application of workflow to modelling and execution of AM processes. Specifically, it will investigate appropriate methodologies in applying workflow techniques to AM frameworks. One of the benefits of applying workflow models to AM processes is to adapt and enable both ad-hoc and evolutionary changes over time. In addition, this can automate an AM process as well as to support the coordination and collaboration of people that are involved in carrying out the process. A workflow management system (WFMS) can be used to support the design and enactment (i.e. execution) of processes and cope with changes that occur to the process during the enactment. So far few literatures can be found in documenting a systematic approach to modelling the characteristics of AM processes. In order to obtain a workflow model for AM processes commonalities and differences between different AM processes need to be identified. This is the fundamental step in developing a conscientious workflow model for AM processes. Therefore, the first stage of this research focuses on identifying the characteristics of AM processes, especially AM decision making processes. The second stage is to review a number of contemporary workflow techniques and choose a suitable technique for application to AM decision making processes. The third stage is to develop an intermediate ameliorated AM decision process definition that improves the current process description and is ready for modelling using the workflow language selected in the previous stage. All these lead to the fourth stage where a workflow model for an AM decision making process is developed. The process model is then deployed (semi-) automatically in a state-of-the-art WFMS demonstrating the benefits of applying workflow technology to the domain of AM. Given that the information in the AM decision making process is captured at an abstract level within the scope of this work, the deployed process model can be used as an executable guideline for carrying out an AM decision process in practice. Moreover, it can be used as a vanilla system that, once being incorporated with rich information from a specific AM decision making process (e.g. in the case of a building construction or a power plant maintenance), is able to support the automation of such a process in a more elaborated way.

Aircraft automation tasks requiring switching control

A key feature in future aircraft operations will be automation of various aircraft processes, such as air traffic separation management and the management of forced landing events. Automated versions of these processes will often involve consideration of multiple modes of operations and hence require consideration of automated decision processes able to switch between various available modes of operations. This paper proposes a switching algorithm on the basis of max-min decision theory. This algorithm is particularly suitable in situations where each operational mode has access to different set of partial information. We apply our proposed algorithm to the air traffic separation management problem. A simulation study is presented that illustrates the performance of the proposed switching algorithm.

Validation and automation of the DYNJAWS component module of the BEAMnrc Monte Carlo code

The purpose of this work is to validate and automate the use of DYNJAWS; a new component module (CM) in the BEAMnrc Monte Carlo (MC) user code. The DYNJAWS CM simulates dynamic wedges and can be used in three modes; dynamic, step-and-shoot and static. The step-and-shoot and dynamic modes require an additional input file defining the positions of the jaw that constitutes the dynamic wedge, at regular intervals during its motion. A method for automating the generation of the input file is presented which will allow for the more efficient use of the DYNJAWS CM. Wedged profiles have been measured and simulated for 6 and 10 MV photons at three field sizes (5 cm x 5 cm , 10 cm x10 cm and 20 cm x 20 cm), four wedge angles (15, 30, 45 and 60 degrees), at dmax and at 10 cm depth. Results of this study show agreement between the measured and the MC profiles to within 3% of absolute dose or 3 mm distance to agreement for all wedge angles at both energies and depths. The gamma analysis suggests that dynamic mode is more accurate than the step-and-shoot mode. The DYNJAWS CM is an important addition to the BEAMnrc code and will enable the MC verification of patient treatments involving dynamic wedges.

Scaling acoustic data analysis through collaboration and automation

Monitoring and assessing environmental health is becoming increasingly important as human activity and climate change place greater pressure on global biodiversity. Acoustic sensors provide the ability to collect data passively, objectively and continuously across large areas for extended periods of time. While these factors make acoustic sensors attractive as autonomous data collectors, there are significant issues associated with large-scale data manipulation and analysis. We present our current research into techniques for analysing large volumes of acoustic data effectively and efficiently. We provide an overview of a novel online acoustic environmental workbench and discuss a number of approaches to scaling analysis of acoustic data; collaboration, manual, automatic and human-in-the loop analysis.

Quantitative fit assessment of a precontoured fracture fixation plate : its automation and an investigation on the borderline cases

Virtual methods to assess the fitting of a fracture fixation plate were proposed recently, however with limitations such as simplified fit criteria or manual data processing. This study aims to automate a fit analysis procedure using clinical-based criteria, and then to analyse the results further for borderline fit cases. Three dimensional (3D) models of 45 bones and of a precontoured distal tibial plate were utilized to assess the fitting of the plate automatically. A Matlab program was developed to automatically measure the shortest distance between the bone and the plate at three regions of interest and a plate-bone angle. The measured values including the fit assessment results were recorded in a spreadsheet as part of the batch-process routine. An automated fit analysis procedure will enable the processing of larger bone datasets in a significantly shorter time, which will provide more representative data of the target population for plate shape design and validation. As a result, better fitting plates can be manufactured and made available to surgeons, thereby reducing the risk and cost associated with complications or corrective procedures. This in turn, is expected to translate into improving patients' quality of life.

Analysing environmental acoustic data through collaboration and automation

Monitoring environmental health is becoming increasingly important as human activity and climate change place greater pressure on global biodiversity. Acoustic sensors provide the ability to collect data passively, objectively and continuously across large areas for extended periods. While these factors make acoustic sensors attractive as autonomous data collectors, there are significant issues associated with large-scale data manipulation and analysis. We present our current research into techniques for analysing large volumes of acoustic data efficiently. We provide an overview of a novel online acoustic environmental workbench and discuss a number of approaches to scaling analysis of acoustic data; online collaboration, manual, automatic and human-in-the loop analysis.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular, and time-varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two nonparametric transforms, namely, rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. The objective is to produce a stereo vision sensor suited to close-range scenes consisting primarily of rocks. This sensor should be able to produce a dense depth map within real-time constraints. Speed and robustness are of foremost importance for this investigation. A number of area based matching metrics have been implemented, including the SAD, SSD, NCC, and their zero-meaned versions. The NCC and the zero meaned SAD and SSD were found to produce the disparity maps with the highest proportion of valid matches. The plain SAD and SSD were the least computationally expensive, due to all their operations taking place in integer arithmetic, however, they were extremely sensitive to radiometric distortion. Non-parametric techniques for matching, in particular, the rank and the census transform, have also been investigated. The rank and census transforms were found to be robust with respect to radiometric distortion, as well as being able to produce disparity maps with a high proportion of valid matches. An additional advantage of both the rank and the census transform is their amenability to fast hardware implementation.