Underground Mining Monitoring and Communication Systems based on ZigBee and GIS

ZigBee as a wireless sensor network (WSN) was developed for underground mine monitoring and communication systems. The radio wave attenuations between ZigBee nodes were investigated to measure underground communication distances. Various sensor node arrangements of ZigBee topologies were evaluated. A system integration of a WSN-assisted GIS for underground mining monitoring and communication from a surface office was proposed. The controllable and uncontrollable parameters of underground environments were assessed to establish a reliable ZigBee network

Data Mining - A Review and Description

Data mining is a powerful and new technique with great potential. It converts the raw data into the useful informati on. Data Mining is the process of extracting knowledge fr om data warehouses. To store databases, enterprises make data warehouses and data marts. Data warehouses and data marts contain large amounts of data. Due to extracting knowledge from large data warehou ses or depositories, data mining plays great role in various fields of machine learning, advancements in static, database system, pattern matching, and artificial intelligence. Various algorithms and programs are used for data mining approach

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

Advanced extravehicular activity systems requirements definition study. Phase 2: Extravehicular activity at a lunar base

The focus is on Extravehicular Activity (EVA) systems requirements definition for an advanced space mission: remote-from-main base EVA on the Moon. The lunar environment, biomedical considerations, appropriate hardware design criteria, hardware and interface requirements, and key technical issues for advanced lunar EVA were examined. Six remote EVA scenarios (three nominal operations and three contingency situations) were developed in considerable detail

IMMERSIVE, INTEROPERABLE AND INTUITIVE MIXED REALITY FOR SERVICE IN INDUSTRIAL PLANTS

The authors propose an innovative Mixed Reality solution representing an immersive intuitive and interoperable environment to support service in industrial plants. These methodologies are related to concepts of Industry 4.0. Solutions based on a mix of VR and AR (Virtual and Augmented Reality ) with special attention to the maintenance of industrial machines; indeed the authors propose an overview of this approach and other synergistic techniques. Moreover, alternative instruments are presented and their specific advantages and disadvantages are described. Particularly, the approach is based on the SPIDER, an advanced interoperable interactive CAVE developed by the authors which supports cooperative work of several users involved in training, troubleshooting and supervision are proposed. Last but not least, an overview of projects using same techniques in other fields, such as construction, risk assessment, Virtual Prototyping and Simulation Based Design is presented

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Formation and mitigation of toxic emissions from blasting in mining: Experimental investigation and development of aerial sampling methods

A key aspect in optimising blasting operations in mining is reducing toxic species in post-blast fumes, notably NOx from ammonium nitrate-based mixes, which pose a direct threat to miners' health and neighbouring settlements. Reducing these pollutants can be done mainly through improving the explosive formulation and blasting practices which in turn require both A) an understanding of the physical and chemical parameters involved and B) the ability to validate any improvement through the direct field-sampling of post-blast fumes. A series of lab-based experiments on the thermal decomposition of ammonium nitrate was carried out with the complete quantification of each product using FTIR, μGC and IC. The physical parameters that varied were temperature, residence time, and whether to have reagents in dry or aqueous forms. The chemical parameters changed were the presence of oxygen gas and urea. The substantial aspect developed in those experiments relates to using high-heating rates believed to be of comparable magnitude to those occurring in blast holes in mining during detonation. The thesis then reports on developing and testing custom-designed drone sampling systems for emissions from blasting operations in mining. The key features in the final aerial sampling system developed (weighing ≤ 10 kg including drone) are i) the fast spectroscopic real-time measurement of NO, NO2, CO, CO2, N2O, NH3, VOCs and PM; and ii) the collection of VOCs and PM2.5 for post-sampling analysis using analytical techniques such as GC-MS and XRD. While sampling in a mine site was not possible, all samplers have been tested with fumes from industrial and transport sources around Perth, Western Australia and a blasting chamber in New South Wales. Two smaller systems (weighing ≤ 2 kg, including drone) sampled air toxics from urban sources

Visualizing Provenance In A Supply chain Using Ethereum Blockchain

Visualization is a widely used in different fields of studies such as supply chain management when there is a need to communicate information to general users. However, there are multiple limitations and problems with visualizing information within traditional systems. In traditional systems, data is in control of one single authority; so data is mutable and there is no guarantee that system administer does not change the data to achieve a desired result. Besides, such systems are not transparent and users do not have any access to the data flow. In this thesis, the main goal was to visualize information that has been saved on top of a new technology named blockchain to overcome the aforementioned problems. All the records in the system are saved on the blockchain and data is pulled out from blockchain to be used in visualization. To have a better insight, a review has been done on relevant studies about blockchain, supply chain and visualization. After identifying the gap in literature review, an architecture was proposed that was used in the implementation. The implementation contains, a system on top of ethereum blockchain and front-end which allows users to interact with the system. In the system, all the information about products and all the transactions that ever happened in the system, are recorded on the blockchain. Then, data was retrieved from the blockchain and used to visualize provenance of products on Google Map API. After implementing the system, the performance was evaluated to make sure that it can handle different situations where various number of clients sending request to the system simultaneously. The performance was as expected in which system responds longer when number of clients sending requests were growing. The proposed solution fill the gap that was identified in the literature review. By adding provenance visualization users can explore previous owners and locations of a product in a trustable manner. Future research can focus on analysis of data which will allow organizations to make informed decisions on choosing popular products to sell

A Tutorial and Future Research for Building a Blockchain-Based Secure Communication Scheme for Internet of Intelligent Things

The Internet of Intelligent Things (IoIT) communication environment can be utilized in various types of applications (for example, intelligent battlefields, smart healthcare systems, the industrial internet, home automation, and many more). Communications that happen in such environments can have different types of security and privacy issues, which can be resolved through the utilization of blockchain. In this paper, we propose a tutorial that aims in desiging a generalized blockchain-based secure authentication key management scheme for the IoIT environment. Moreover, some issues with using blockchain for a communication environment are discussed as future research directions. The details of different types of blockchain are also provided. Some of the widely-accepted consensus algorithms are then discussed. Next, we discuss different types of applications in blockchain-based IoIT communication environments. The details of the associated system models are provided, such as, the network and attack models for the blockchain-based IoIT communication environment, which are helpful in designing a security protocol for such an environment. A practical demonstration of the proposed generalized scheme is provided in order to measure the impact of the scheme on the performance of the essential parameters. Finally, some of the future research challenges in the blockchain-based IoIT communication environment are highlighted, which will also be helpful to the researchers