337 research outputs found

    Command and Control Systems for Search and Rescue Robots

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    The novel application of unmanned systems in the domain of humanitarian Search and Rescue (SAR) operations has created a need to develop specific multi-Robot Command and Control (RC2) systems. This societal application of robotics requires human-robot interfaces for controlling a large fleet of heterogeneous robots deployed in multiple domains of operation (ground, aerial and marine). This chapter provides an overview of the Command, Control and Intelligence (C2I) system developed within the scope of Integrated Components for Assisted Rescue and Unmanned Search operations (ICARUS). The life cycle of the system begins with a description of use cases and the deployment scenarios in collaboration with SAR teams as end-users. This is followed by an illustration of the system design and architecture, core technologies used in implementing the C2I, iterative integration phases with field deployments for evaluating and improving the system. The main subcomponents consist of a central Mission Planning and Coordination System (MPCS), field Robot Command and Control (RC2) subsystems with a portable force-feedback exoskeleton interface for robot arm tele-manipulation and field mobile devices. The distribution of these C2I subsystems with their communication links for unmanned SAR operations is described in detail. Field demonstrations of the C2I system with SAR personnel assisted by unmanned systems provide an outlook for implementing such systems into mainstream SAR operations in the future

    Workshop sensing a changing world : proceedings workshop November 19-21, 2008

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    Advances in Grid Computing

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    This book approaches the grid computing with a perspective on the latest achievements in the field, providing an insight into the current research trends and advances, and presenting a large range of innovative research papers. The topics covered in this book include resource and data management, grid architectures and development, and grid-enabled applications. New ideas employing heuristic methods from swarm intelligence or genetic algorithm and quantum encryption are considered in order to explain two main aspects of grid computing: resource management and data management. The book addresses also some aspects of grid computing that regard architecture and development, and includes a diverse range of applications for grid computing, including possible human grid computing system, simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems

    The selection and evaluation of a sensory technology for interaction in a warehouse environment

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    In recent years, Human-Computer Interaction (HCI) has become a significant part of modern life as it has improved human performance in the completion of daily tasks in using computerised systems. The increase in the variety of bio-sensing and wearable technologies on the market has propelled designers towards designing more efficient, effective and fully natural User-Interfaces (UI), such as the Brain-Computer Interface (BCI) and the Muscle-Computer Interface (MCI). BCI and MCI have been used for various purposes, such as controlling wheelchairs, piloting drones, providing alphanumeric inputs into a system and improving sports performance. Various challenges are experienced by workers in a warehouse environment. Because they often have to carry objects (referred to as hands-full) it is difficult to interact with traditional devices. Noise undeniably exists in some industrial environments and it is known as a major factor that causes communication problems. This has reduced the popularity of using verbal interfaces with computer applications, such as Warehouse Management Systems. Another factor that effects the performance of workers are action slips caused by a lack of concentration during, for example, routine picking activities. This can have a negative impact on job performance and allow a worker to incorrectly execute a task in a warehouse environment. This research project investigated the current challenges workers experience in a warehouse environment and the technologies utilised in this environment. The latest automation and identification systems and technologies are identified and discussed, specifically the technologies which have addressed known problems. Sensory technologies were identified that enable interaction between a human and a computerised warehouse environment. Biological and natural behaviours of humans which are applicable in the interaction with a computerised environment were described and discussed. The interactive behaviours included the visionary, auditory, speech production and physiological movement where other natural human behaviours such paying attention, action slips and the action of counting items were investigated. A number of modern sensory technologies, devices and techniques for HCI were identified with the aim of selecting and evaluating an appropriate sensory technology for MCI. iii MCI technologies enable a computer system to recognise hand and other gestures of a user, creating means of direct interaction between a user and a computer as they are able to detect specific features extracted from a specific biological or physiological activity. Thereafter, Machine Learning (ML) is applied in order to train a computer system to detect these features and convert them to a computer interface. An application of biomedical signals (bio-signals) in HCI using a MYO Armband for MCI is presented. An MCI prototype (MCIp) was developed and implemented to allow a user to provide input to an HCI, in a hands-free and hands-full situation. The MCIp was designed and developed to recognise the hand-finger gestures of a person when both hands are free or when holding an object, such a cardboard box. The MCIp applies an Artificial Neural Network (ANN) to classify features extracted from the surface Electromyography signals acquired by the MYO Armband around the forearm muscle. The MCIp provided the results of data classification for gesture recognition to an accuracy level of 34.87% with a hands-free situation. This was done by employing the ANN. The MCIp, furthermore, enabled users to provide numeric inputs to the MCIp system hands-full with an accuracy of 59.7% after a training session for each gesture of only 10 seconds. The results were obtained using eight participants. Similar experimentation with the MYO Armband has not been found to be reported in any literature at submission of this document. Based on this novel experimentation, the main contribution of this research study is a suggestion that the application of a MYO Armband, as a commercially available muscle-sensing device on the market, has the potential as an MCI to recognise the finger gestures hands-free and hands-full. An accurate MCI can increase the efficiency and effectiveness of an HCI tool when it is applied to different applications in a warehouse where noise and hands-full activities pose a challenge. Future work to improve its accuracy is proposed

    Energy Efficiency in Communications and Networks

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    The topic of "Energy Efficiency in Communications and Networks" attracts growing attention due to economical and environmental reasons. The amount of power consumed by information and communication technologies (ICT) is rapidly increasing, as well as the energy bill of service providers. According to a number of studies, ICT alone is responsible for a percentage which varies from 2% to 10% of the world power consumption. Thus, driving rising cost and sustainability concerns about the energy footprint of the IT infrastructure. Energy-efficiency is an aspect that until recently was only considered for battery driven devices. Today we see energy-efficiency becoming a pervasive issue that will need to be considered in all technology areas from device technology to systems management. This book is seeking to provide a compilation of novel research contributions on hardware design, architectures, protocols and algorithms that will improve the energy efficiency of communication devices and networks and lead to a more energy proportional technology infrastructure

    Development of an open-source mobile application for emergency data collection

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    This Master degree project identified disasters and emergencies as a global humanitarian and technological challenge. Emergency management organizations' need for access to accurate and up-to-date information about the emergency situation, to help respond to, recover from and mitigate the effects of disasters and emergencies, presents a challenge to the field of Geomatics. Today the use of remote sensing technologies presents an increasing number of solutions. There are types of spatial data, however, e.g. submerged, non-visual or otherwise hidden features that still require emergency field personnel and volunteers to interpret and record. By utilizing the increasing ubiquity and computational power of modern smartphones, in order to reach a large number of potential users and volunteers, a mobile application for emergency field data collection was developed. It was developed as a component of a system that, in order to be as collaborative, adaptable and accessible as possible, also to resource-poor organizations, was, with a minor exception, completely open-source licensed. Field trials were held that, due to low participation, could not conclusively evaluate the application and its general applicability to emergency field data collection. They did, however, provide an adequate proof-of-concept and showed that it was possible to apply the application and the implemented system to a specific emergency field data collection task. The system has great collaborative potential, achieved through openness, mobility, standards compliance, multi-source capability and adaptability. Its administrators are given a high degree of control that lets them adapt the system to suit the current users and situation and its flexibility make it widely applicable, not only for emergency management. From literature, the field trials and the experience gained while developing and using the application, some ideas for improving the application and the system were discussed and some future research topics were suggested.Under och efter katastrofer och nödsituationer samlas mĂ„nga olika organisationer för att hjĂ€lpa de drabbade. Det kan vara t.ex. polis, brandkĂ„r, sjukvĂ„rd, eller elbolag som mĂ„ste reparera ledningsnĂ€t. Vid större katastrofer kan myndigheter och internationella hjĂ€lporganisationer ocksĂ„ behöva komma till undsĂ€ttning. För att dessa organisationer ska kunna hjĂ€lpa till pĂ„ ett effektivt sĂ€tt mĂ„ste de ha tillgĂ„ng till uppdaterad och korrekt information om krislĂ€get. En stor del av den hĂ€r informationen Ă€r kopplad till en specifik plats; den Ă€r geografisk. Idag fĂ„r organisationer som jobbar med krishantering mycket av sin geografiska information frĂ„n satelliter och flygbilder, men en del typer av information kan inte ses med satellit. Dessa kan vara t.ex. ledningar som ligger begravda under markytan eller mĂ€nskliga skador och behov. DĂ€rför behövs ocksĂ„ nĂ„gon form av system som personal och volontĂ€rer i fĂ€lt kan anvĂ€nda för att rapportera till krisledningscentraler pĂ„ ett effektivt sĂ€tt. MĂ„nga sĂ„dana system har historiskt sett varit dyra att skaffa eftersom de krĂ€vt avancerade datorprogram och dyr teknisk utrustning till personalen i fĂ€lt. Eftersom de dessutom mĂ„nga gĂ„nger varit svĂ„ra att anvĂ€nda har det varit svĂ„rt för krishanterings-organisationer att fĂ„ ihop tillrĂ€ckligt mĂ„nga personer att hjĂ€lpa till. Det hĂ€r projektet syftade till att utveckla en mobil-app, d.v.s. ett program till moderna mobiltelefoner (s.k. smartphones). MĂ„let med appen var att alla som Ă€ger en smartphone av rĂ€tt typ skulle kunna bidra till att samla viktig geografisk information till krisledningscentralen. Genom att lĂ„ta appen vara en del av ett system som Ă€r helt gratis att anvĂ€nda och med öppen kĂ€llkod, kan Ă€ven organisationer med smĂ„ resurser och lite pengar anvĂ€nda den. Tack vare att sĂ„ mĂ„nga redan Ă€ger smartphones som de dessutom redan Ă€r vana vid att anvĂ€nda kan det bli lĂ€ttare att fĂ„ fler att kunna medverka. Utvecklingen av appen lyckades och hela systemet Ă€r gratis att anvĂ€nda och utgivet – nĂ€stan – helt med öppen kĂ€llkod. Appen testades, men av för fĂ„ deltagare för att kunna dra nĂ„gra definitiva slutsatser om systemet Ă€r lĂ€mpligt att anvĂ€nda för krishantering. Dock visade appen och systemet god potential under testerna och att det var möjligt att anvĂ€nda appen för att samla information i en katastrofsituation

    Experimental Evaluation of Spectrum Sensing Algorithms for Wireless Microphone Signal

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    Spectrum congestion has become a critical concern in wireless communication systems due to the limited availability of frequency spectrum. Hence, efficient utilization of spectrum is one of the most important challenges in the evolution of wireless communi-cation systems and radio devices. Cognitive radio (CR) has been introduced as an effec-tive solution for spectrum utilization. Spectrum sensing (SS) is one of the key elements in the implementation of effective and reliable CR systems. SS algorithms are used to obtain awareness about the spectrum usage and existence of primary users in a certain spectrum band. Energy detection (ED) based SS is the most common sensing algorithm due to its low computation and implementation complexity. On the other hand, ED based SS is highly dependent on the precise knowledge of the receiver noise variance. Hence, the performance of the ED algorithm is degraded significantly, when there is uncertainty in the estimation of the noise variance. In this thesis, the wireless microphone (WM) system using the CR concept is intro-duced and the sensing performance of WM signals using three different algorithms are studied. The considered algorithms are based on the ED, namely fast Fourier transform (FFT) based ED, analysis filter bank (AFB) based ED and maximum-minimum ED (Max-Min ED) are studied. Following the analytical models and scenarios of energy detector based SS algorithms, the sensing algorithms are implemented using National Instruments’ (NI) Universal Software Radio Peripheral (USRP) and the NI-LabVIEW software platform, together with the necessary toolboxes. This prototype implementa-tion provides reliable performance evaluation of these spectrum sensing approaches us-ing real world receiver implementation and communication signals from a signal genera-tor, as well as actual WM signals. The results of this study suggest that the performance of Max-Min ED is more robust than FFT & AFB based ED under realistic noise vari-ance uncertainty

    Low-Power Wireless Medical Systems and Circuits for Invasive and Non-Invasive Applications

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    Approximately 75% of the health care yearly budget of public health systems around the world is spent on the treatment of patients with chronic diseases. This, along with advances on the medical and technological fields has given rise to the use of preventive medicine, resulting on a high demand of wireless medical systems (WMS) for patient monitoring and drug safety research. In this dissertation, the main design challenges and solutions for designing a WMS are addressed from system-level, using off-the-shell components, to circuit implementation. Two low-power oriented WMS aiming to monitor blood pressure of small laboratory animals (implantable) and cardiac-activity (12-lead electrocardiogram) of patients with chronic diseases (wearable) are presented. A power consumption vs. lifetime analysis to estimate the monitoring unit lifetime for each application is included. For the invasive/non-invasive WMS, in-vitro test benches are used to verify their functionality showing successful communication up to 2.1 m/35 m with the monitoring unit consuming 0.572 mA/33 mA from a 3 V/4.5 V power supply, allowing a two-year/ 88-hour lifetime in periodic/continuous operation. This results in an improvement of more than 50% compared with the lifetime commercial products. Additionally, this dissertation proposes transistor-level implementations of an ultra-low-noise/low-power biopotential amplifier and the baseband section of a wireless receiver, consisting of a channel selection filter (CSF) and a variable gain amplifier (VGA). The proposed biopotential amplifier is intended for electrocardiogram (ECG)/ electroencephalogram (EEG)/ electromyogram (EMG) monitoring applications and its architecture was designed focused on improving its noise/power efficiency. It was implemented using the ON-SEMI 0.5 ”m standard process with an effective area of 360 ”m2. Experimental results show a pass-band gain of 40.2 dB (240 mHz - 170 Hz), input referred noise of 0.47 Vrms, minimum CMRR of 84.3 dBm, NEF of 1.88 and a power dissipation of 3.5 ”W. The CSF was implemented using an active-RC 4th order inverse-chebyshev topology. The VGA provides 30 gain steps and includes a DC-cancellation loop to avoid saturation on the sub-sequent analog-to-digital converter block. Measurement results show a power consumption of 18.75 mW, IIP3 of 27.1 dBm, channel rejection better than 50 dB, gain variation of 0-60dB, cut-off frequency tuning of 1.1-2.29 MHz and noise figure of 33.25 dB. The circuit was implemented in the standard IBM 0.18 ”m CMOS process with a total area of 1.45 x 1.4 mm^(2). The presented WMS can integrate the proposed biopotential amplifier and baseband section with small modifications depending on the target signal while using the low-power-oriented algorithm to obtain further power optimization
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