A Feasibility Study of a Persistent Monitoring System for the Flight Deck of U.S. Navy Aircraft Carriers

This research analyzes the use of modern Real Time Locating Systems (RTLS), such as the Global Positioning System (GPS), to improve the safety of aircraft, equipment, and personnel onboard a United States Navy (USN) aircraft carrier. The results of a detailed analysis of USN safety records since 1980 show that mishaps which could potentially be prevented by a persistent monitoring system result in the death of a sailor nearly every other year and account for at least $92,486,469, or 5.55% of the total cost of all flight deck and hangar bay related mishaps. A system to continually monitor flight deck operations is proposed with four successive levels of increasing capability. A study of past and present work in the area of aircraft carrier flight deck operations is performed. This research conducted a study of the movements of USN personnel and an FA-18C aircraft being towed at NAS Oceana, VA. Using two precision GPS recorders mounted on the aircraft wingtips, the position and orientation of the aircraft, in two-dimensions, are calculated and the errors in this solution are explored. The distance between personnel and the aircraft is calculated in the nearest neighbor sense. Pseudospectral motion planning techniques are presented to provide route prediction for aircraft, support equipment, and personnel. Concepts for system components, such as aircraft and personnel receivers, are described. Methods to recognize and communicate the presence of hazardous situations are discussed. The end result of this research is the identification of performance requirements, limitations, and definition of areas of further research for the development of a flight deck persistent monitoring system with the capability to warn of hazardous situations, ease the incorporation of UAVs, and reduce the risk of death or injury faced by sailors on the flight deck

Opportunity Knocks: A System to Provide Cognitive Assistance with Transportation Services

We present an automated transportation routing system, called “Opportunity Knocks,” whose goal is to improve the efficiency, safety and independence of individuals with mild cognitive disabilities. Our system is implemented on a combination of a Bluetooth sensor beacon that broadcasts GPS data, a GPRS-enabled cell-phone, and remote activity inference software. The system uses a novel inference engine that does not require users to explicitly provide information about the start or ending points of their journeys; instead this information is learned from users’ past behavior. Futhermore, we demonstrate how route errors can be detected and how the system helps to correct the errors with real-time transit information. In addition we present a novel solution to the problem of labeling positions with place names.Engineering and Applied Science

Simulation of product transportation in open pit mines

A research report submitted to the Faculty of Engineering and Built Environment, University of Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Masters of Science in Engineering Johannesburg, 2015Open pit mines account for more than 60 percent of all surface mines, and haulage costs account for almost 60 percent of total operating costs for these mines. It necessitates maintaining an efficient haulage system where all fleet equipment performs effectively to achieve the mine’s objectives. Discrete event simulation supported by animation offers a powerful method for evaluating such systems. This research has developed a simulation software program using Visual Basic for Application (VBA), GPSS/H (General Purpose Simulation System), and PROOF 5 animation. Remaining within the defined assumptions and boundary conditions, the research combines the powers of three software languages to build a general-purpose, data-driven, and user-friendly simulation program. The research focuses on the study and simulation of some of the important complexities of the truck haulage system. These include uncertainty or system randomness, fleet heterogeneity, multi-loader multi-dump sites, bunching of haulers, and hauler dispatching. In the developed simulation program, the user is required to provide the inputs in the user-friendly environment of VBA. The simulation program arranges the inputs in a pre-arranged format and then sends them to GPSS/H. The simulation language generates a discrete event simulation model based on the receiving structural and operational data. After simulating the system, the model generates the simulation outputs and animation commands in separate files. VBA displays a summary of the simulation results, and PROOF 5 demonstrates the results in a 2-dimensional graphical animation along with detailed information. This research also includes three case studies based on hypothetical mines for the analysis of simulation results. It establishes comparisons between the dispatching policies of fixed allocation and variable allocation of Minimize Production Requirements (MPR), and shows that the MPR policy is more suitable to achieve the quality control objectives. The developed simulation program contributes by demonstrating the powers of simulation to analyse open pit haulage systems. It also shows how simulation can be utilized as a useful technique to answer many ‘what-if?’ questions and scenarios

Self-Reliance for the Internet of Things: Blockchains and Deep Learning on Low-Power IoT Devices

The rise of the Internet of Things (IoT) has transformed common embedded devices from isolated objects to interconnected devices, allowing multiple applications for smart cities, smart logistics, and digital health, to name but a few. These Internet-enabled embedded devices have sensors and actuators interacting in the real world. The IoT interactions produce an enormous amount of data typically stored on cloud services due to the resource limitations of IoT devices. These limitations have made IoT applications highly dependent on cloud services. However, cloud services face several challenges, especially in terms of communication, energy, scalability, and transparency regarding their information storage. In this thesis, we study how to enable the next generation of IoT systems with transaction automation and machine learning capabilities with a reduced reliance on cloud communication. To achieve this, we look into architectures and algorithms for data provenance, automation, and machine learning that are conventionally running on powerful high-end devices. We redesign and tailor these architectures and algorithms to low-power IoT, balancing the computational, energy, and memory requirements.The thesis is divided into three parts:Part I presents an overview of the thesis and states four research questions addressed in later chapters.Part II investigates and demonstrates the feasibility of data provenance and transaction automation with blockchains and smart contracts on IoT devices.Part III investigates and demonstrates the feasibility of deep learning on low-power IoT devices.We provide experimental results for all high-level proposed architectures and methods. Our results show that algorithms of high-end cloud nodes can be tailored to IoT devices, and we quantify the main trade-offs in terms of memory, computation, and energy consumption

Intelligent Mobility in Smart Cities

Smart Cities seek to optimize their systems by increasing integration through approaches such as increased interoperability, seamless system integration, and automation. Thus, they have the potential to deliver substantial efficiency gains and eliminate redundancy. To add to the complexity of the problem, the integration of systems for efficiency gains may compromise the resilience of an urban system. This all needs to be taken into consideration when thinking about Smart Cities. The transportation field must also apply the principles and concepts mentioned above. This cannot be understood without considering its links and effects on the other components of an urban system. New technologies allow for new means of travel to be built, and new business models allow for existing ones to be utilized. This Special Issue puts together papers with different focuses, but all of them tackle the topic of smart mobility

e-Sanctuary: open multi-physics framework for modelling wildfire urban evacuation

The number of evacuees worldwide during wildfire keep rising, year after year. Fire evacuations at the wildland-urban interfaces (WUI) pose a serious challenge to fire and emergency services and are a global issue affecting thousands of communities around the world. But to date, there is a lack of comprehensive tools able to inform, train or aid the evacuation response and the decision making in case of wildfire. The present work describes a novel framework for modelling wildfire urban evacuations. The framework is based on multi-physics simulations that can quantify the evacuation performance. The work argues that an integrated approached requires considering and integrating all three important components of WUI evacuation, namely: fire spread, pedestrian movement, and traffic movement. The report includes a systematic review of each model component, and the key features needed for the integration into a comprehensive toolkit

Spatio-temporal Modelling of Accessibility to Train Stations for Park and Ride (PnR) Users

Accessibility has been of critical importance to physical planning over the past 60 years. This study mainly focuses a spatial methodology framework to understand measure and model the Park and Ride (PnR) users’ accessibility to train stations, specifically including the characteristics of catchment areas, directional accessibility to train stations, spatial modelling of train stations’ catchment areas, and spatio-temporal modelling of accessibility to train stations