Towards a digital mine: a spatial database for accessing historical geospatial data on mining and related activities

A Research Report submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science. Johannesburg, 2016.Countries around the world are recognising the importance of geospatial data in answering questions related to spatially varying industries such as mining activities (ongoing and discontinued). This is becoming increasingly evident with countries such as Canada, Australia, and the United Kingdom working towards establishing Abandoned Mine Lands (AML) inventories. However, the increasing need for data on mining activities is not paralleled by an increase in the availability of such data. The aim of this research therefore is to design a database for accessing historical and current geospatial data that can be used to support research, environmental management efforts as well as support decision making at all levels. A user needs survey was conducted. Two sampling methods were employed, convenient sampling and snowball sampling method. The convenient sampling method was used mostly with all the WDMP group members and the latter was employed with the respondents from institutions and organisations outside of the university respectively. The data were then categorised so as to make analysis easier and data could be evaluated on the same basis. An evaluation of the data collected showed that although the WDMP required different types of data (spatial and non- spatial) the data feed into each other and as such it is important that there is a central repository in which to store them. Furthermore investigation also shows that there is a wealth of data on current mining activities, but not so much on historical mining activities. Although data on mining activities exists, accessibility to these data is hindered by various factors such as copyright infringements, data costs, discrepancies in the data request process. The outcome of this research has been that of a physical database PostgreSQL database (PostGIS) and one mounted on an online platform (GeoServer). The databases can be visualised on PostgreSQL using select statements or visualisation through establishing a connection with QGIS, alternatively the database may be accessed on GeoServer. The database is expected to be of use to at least all members of the Wits Digital Mine Project (WDMP) and stakeholders involved in the project. The database can be used for baseline studies and also as a basis for the framework used to analyse, remedy as well as predict future challenges in the mining industry. Moreover, the database can act as a central repository for all data produced from the WDMP.LG201

Hardware design for in-mine positioning system

This thesis describes the hardware design of a positioning system which locates a vehicle relative to a digital map of an underground mine. The mines of interest are potash mines of Saskatchewan, and they are at a depth of approximately 1000 meters and they cover an area larger than 10 kilometers by 10 kilometers. An important application of an in-mine positioning system is tracking a ground penetrating radar system. Ground penetrating radar is used to determine the current condition of the mine ceiling and to evaluate its risk of delamination. A ground penetrating radar system is driven along a mine tunnel and measurements are logged. It is necessary to record position information along with the radar signal and this can be done with the aid of a positioning system. The design and evaluation of the hardware system that supports a positioning system, which can locate a vehicle inside a mine tunnel with reasonable accuracy and cost is described in this thesis. The hardware system includes a dead reckoning system (DRS), which is built using MEMS (Micro Electro Mechanical System) accelerometer and gyroscope sensors and ultrasonic distance sensors, along with a data acquisition system

3D MODELING AND PRODUCTION SCHEDULING OF KHEWRA SALT MINES

In this study, AutoCAD based 3D Modelling of production scheduling, visualization of mining, and geological features in Khewra Salt Mines are showing. Unmanned Aerial Vehicle (UAV), photogrammetry and GIS Softwares are used to generate 3D surface modelling of Khewra Salt Mining Area. Khewra Salt Mines is the oldest and largest mine of sub-continent in the Salt Range with huge salt reserves from industrial quality to piece grade. Being a state-of-the-art mine consisting of 17 levels, 70 chambers with hundreds of tunnels, a layman pattern of development and manual mining procedure is followed with handy-made planes and maps. Hundreds of levels and cross-section maps were unified to a single 3D Model, presenting all mining features like tunnels, chambers, levels, inclines, and geological deposition of different salt seams with their thickness and qualities, overburden, and surface feature. The quantity of salt excavated since the beginning of mining is calculated for corroboration, and the remaining amounts of different qualities of salt are determined from the model. 3D topographic Modelling can also be used for area, volume calculations, and planning of remedial actions for rainwater inundations inside the mine

Low-cost sensors technologies for monitoring sustainability and safety issues in mining activities: advances, gaps, and future directions in the digitalization for smart mining

Nowadays, monitoring aspects related to sustainability and safety in mining activities worldwide are a priority, to mitigate socio-environmental impacts, promote efficient use of water, reduce carbon footprint, use renewable energies, reduce mine waste, and minimize the risks of accidents and fatalities. In this context, the implementation of sensor technologies is an attractive alternative for the mining industry in the current digitalization context. To have a digital mine, sensors are essential and form the basis of Industry 4.0, and to allow a more accelerated, reliable, and massive digital transformation, low-cost sensor technology solutions may help to achieve these goals. This article focuses on studying the state of the art of implementing low-cost sensor technologies to monitor sustainability and safety aspects in mining activities, through the review of scientific literature. The methodology applied in this article was carried out by means of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and generating science mapping. For this, a methodological procedure of three steps was implemented: (i) Bibliometric analysis as a quantitative method, (ii) Systematic review of literature as a qualitative method, and (iii) Mixed review as a method to integrate the findings found in (i) and (ii). Finally, according to the results obtained, the main advances, gaps, and future directions in the implementation of low-cost sensor technologies for use in smart mining are exposed. Digital transformation aspects for data measurement with low-cost sensors by real-time monitoring, use of wireless network systems, artificial intelligence, machine learning, digital twins, and the Internet of Things, among other technologies of the Industry 4.0 era are discussed.The authors are indebted to the projects PID2021-126405OB-C31 and PID2021-126405OB-C32 funded by FEDER funds—A Way to Make Europe and Spanish Ministry of Economy and Competitiveness MICIN/AEI/10.13039/501100011033/. The financial support of the Research Department of the Catholic University of Temuco and the Civil Engineering Department of the University of Castilla-La Mancha is also appreciated.Peer ReviewedPostprint (published version

Towards a dynamic capabilities view on ecosystem formation: A case study on the emergence of an innovation ecosystem

Digitalization is a catalyser that drives rapid changes in industries. While bringing huge opportunities for business, digitalization outdated existing capabilities and working methods, thus, it brings threats to companies who cannot timely innovate themselves. In today’s business landscape, no company has sufficient resources to develop digital innovation alone. Companies have to be able to attract, secure and combine a variety of new resources and competencies from other organizations to co-create new services on top of its technology platform. Currently, we see that innovation ecosystems are emerging to answer to this need. Innovation ecosystems are inherently complex as they consist of multiple actors coming from different cultural, political, economical and knowledge backgrounds. Thus, developing innovation ecosystems can be very challenging. However, we have not been equipped with sufficient theoretical and practical knowledge to understand how a company can form an innovation ecosystem. Therefore, this thesis was set to establish a deeper understanding of the factors and capabilities that support the formation of an innovation ecosystem. Through an extensive literature review of both fields - ecosystem and dynamic capabilities, this thesis established the first theoretical model that explains the development of an innovation ecosystem. This theoretical model was applied and developed iteratively in an in-depth case study of a European-based Intelligent Mine innovation ecosystem. This thesis was conducted using an exploratoratory, qualitative approach and followed an abductive research design. Data was collected through several open-ended interviews with ecosystem members and analyzed following Gioia methodology. The results of this thesis shed light on: (1) the key factors that trigger the formation of an innovation ecosystem, (2) the motivations of a hub company for forming an innovation ecosystem, and (3) the sensing and seizing mechanisms that a hub company employed while forming its innovation ecosystem. Moreover, a conceptual model was developed after refining the initial theoretical with new empirical insights. This thesis contributes directly to the development of new theory on ecosystem formation and the new application of dynamic capabilities framework in ecosystem literature. It also provides useful suggestions for companies whose aspiration is to develop innovation ecosystems around their core technologies

Highly efficient computer oriented octree data structure and neighbors search in 3D GIS spatial

Three Dimensional (3D) have given new perspective in various field such as urban planning, hydrology, infrastructure modeling, geology etc due to its capability of handling real world object in more realistic manners, rather than two-dimensional (2D) approach. However, implementation of 3D spatial analysis in the real world has proven difficult due to the complexity of algorithm, computational power and time consuming. Existing GIS system enables 2D and two-and-a-half dimensional (2.5D) spatial datasets, but less capable of supporting 3D data structures. Recent development in Octree see more effort to improve weakness of octree in finding neighbor node by using various address encoding scheme with specific rule to eliminate the need of tree traversal. This paper proposed a new method to speed up neighbor searching and eliminating the needs of complex operation to extract spatial information from octree by preserving 3D spatial information directly from Octree data structure. This new method able to achieve O(1) complexity and utilizing Bit Manipulation Instruction 2 (BMI2) to speedup address encoding, extraction and voxel search 700% compared with generic implementation

Creation and delivery of a complex 3D geological survey for the Glasgow area and its application to urban geology

The Glasgow area has a combination of highly variable superficial deposits and a legacy of heavy industry, quarrying and mining. These factors create complex foundation and hydrological conditions, influencing the movement of contaminants through the subsurface and giving rise locally to unstable ground conditions. Digital geological three-dimensional models developed by the British Geological Survey are helping to resolve the complex geology underlying Glasgow, providing a key tool for planning and environmental management. The models, covering an area of 3200km2 to a depth of 1.2km, include glacial and post-glacial deposits and the underlying, faulted Carboniferous igneous and sedimentary rocks. Control data, including 95,000 boreholes, digital mine plans and published geological maps, were used in model development. Digital outputs from the models include maps of depth to key horizons, such as rockhead or depth to mine workings. The models have formed the basis for the development of site-scale high-resolution geological models and provide input data for a wide range of other applications from groundwater modelling to stochastic lithological modelling

PARADIS: A Prototype for Assisting Rational Activities in Humanitarian Demining Using Images from Satellites

The PARADIS project aims to improve the planning of humanitarian demining campaigns with a software package working from the country scale to the field scale. A demining organization and an image interpretation team work together to put this system to use and benefit mine-affected areas