23 research outputs found

    Collaborative Indoor Positioning Systems: A Systematic Review

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    Research and development in Collaborative Indoor Positioning Systems (CIPSs) is growing steadily due to their potential to improve on the performance of their non-collaborative counterparts. In contrast to the outdoors scenario, where Global Navigation Satellite System is widely adopted, in (collaborative) indoor positioning systems a large variety of technologies, techniques, and methods is being used. Moreover, the diversity of evaluation procedures and scenarios hinders a direct comparison. This paper presents a systematic review that gives a general view of the current CIPSs. A total of 84 works, published between 2006 and 2020, have been identified. These articles were analyzed and classified according to the described system’s architecture, infrastructure, technologies, techniques, methods, and evaluation. The results indicate a growing interest in collaborative positioning, and the trend tend to be towards the use of distributed architectures and infrastructure-less systems. Moreover, the most used technologies to determine the collaborative positioning between users are wireless communication technologies (Wi-Fi, Ultra-WideBand, and Bluetooth). The predominant collaborative positioning techniques are Received Signal Strength Indication, Fingerprinting, and Time of Arrival/Flight, and the collaborative methods are particle filters, Belief Propagation, Extended Kalman Filter, and Least Squares. Simulations are used as the main evaluation procedure. On the basis of the analysis and results, several promising future research avenues and gaps in research were identified

    QoS Assessment and Modelling of Connected Vehicle Network within Internet of Vehicles

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    Connected vehicles have huge potential in improving road safety and traffic congestion. The primary aim of this paper is threefold: firstly to present an overview of network models in connected vehicles; secondly to analyze the factors that impact the Quality of Service (QoS) of connected vehicles and thirdly to present initial modelling results on Link QoS. We use the open access Geometry-based Efficient Propagation Model (GEMV2 ) data to carry out Analysis of Variance, Principal Component Analysis and Classical Multi-Dimensional scaling on the link quality for vehicle-2-vehicle (V2V) and vehicle-2-infrastucture (V2i) data and found that both line of sight and non-line of sight has a significant impact on the link quality. We further carried out modelling using system identification method of the connected vehicle network (CVN) in terms of Link QoS based on the parameters identified by the QoS assessment. We evaluated the CVN in terms of a step response achieving steady-state within 80 seconds for V2V data and 500 seconds for V2i data. The work presented here will further help in the development of CVN prediction model and control for V2V and vehicle-2-anything connectivity

    Assessing Contact Graph Routing Performance and Reliability in Distributed Satellite Constellations

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    A robust predictive control for a Quadrotor with an Airsoft-marker

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    This project is part of a more ambitious European project which consists on the autonomous inspection of petrol pipes. This inspection is done using a custom design drone equipped with a direction system, called gimbal, that allows changing the direction of a set of tools attached to the drone. These tools are a stereo vision system and an airsoft marker, which have special bullets that are used to detect the possible leaks in the pipes in order to fix them. Moreover, the shooting power of the marker can change to adjust according the distance of the pipe. However, the marker introduce into the system an unknown disturbance that can destabilize the drone. Therefore, the main goal of the project is to propose a model predictive controller for the drone. As a first step needed, the project come up with a mathematical model of the drone, specifically a Quadrotor. Also, it is described a way of modeling the Airsoft marker as a disturbance. Then, this model is used in the MPC to calculate the exact control action for satisfying the optimization law, that it is tuned to find a balance between the desired performance and the energy used by the actuators. Finally, a case scenarios is simulated to show how perform the designed controller and the different commands ( roll, pitch and yaw )

    An Approach to Guide Users Towards Less Revealing Internet Browsers

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    When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Previous research has shown that there are numerous privacy and security risks result from exposing sensitive information in the User-Agent string. For example, it enables device and browser fingerprinting and user tracking and identification. Our large analysis of thousands of User-Agent strings shows that browsers differ tremendously in the amount of information they include in their User-Agent strings. As such, our work aims at guiding users towards using less exposing browsers. In doing so, we propose to assign an exposure score to browsers based on the information they expose and vulnerability records. Thus, our contribution in this work is as follows: first, provide a full implementation that is ready to be deployed and used by users. Second, conduct a user study to identify the effectiveness and limitations of our proposed approach. Our implementation is based on using more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available and the solution has been deployed

    Artificial Intelligence and Ambient Intelligence

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    This book includes a series of scientific papers published in the Special Issue on Artificial Intelligence and Ambient Intelligence at the journal Electronics MDPI. The book starts with an opinion paper on “Relations between Electronics, Artificial Intelligence and Information Society through Information Society Rules”, presenting relations between information society, electronics and artificial intelligence mainly through twenty-four IS laws. After that, the book continues with a series of technical papers that present applications of Artificial Intelligence and Ambient Intelligence in a variety of fields including affective computing, privacy and security in smart environments, and robotics. More specifically, the first part presents usage of Artificial Intelligence (AI) methods in combination with wearable devices (e.g., smartphones and wristbands) for recognizing human psychological states (e.g., emotions and cognitive load). The second part presents usage of AI methods in combination with laser sensors or Wi-Fi signals for improving security in smart buildings by identifying and counting the number of visitors. The last part presents usage of AI methods in robotics for improving robots’ ability for object gripping manipulation and perception. The language of the book is rather technical, thus the intended audience are scientists and researchers who have at least some basic knowledge in computer science

    Image and Video Forensics

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    Nowadays, images and videos have become the main modalities of information being exchanged in everyday life, and their pervasiveness has led the image forensics community to question their reliability, integrity, confidentiality, and security. Multimedia contents are generated in many different ways through the use of consumer electronics and high-quality digital imaging devices, such as smartphones, digital cameras, tablets, and wearable and IoT devices. The ever-increasing convenience of image acquisition has facilitated instant distribution and sharing of digital images on digital social platforms, determining a great amount of exchange data. Moreover, the pervasiveness of powerful image editing tools has allowed the manipulation of digital images for malicious or criminal ends, up to the creation of synthesized images and videos with the use of deep learning techniques. In response to these threats, the multimedia forensics community has produced major research efforts regarding the identification of the source and the detection of manipulation. In all cases (e.g., forensic investigations, fake news debunking, information warfare, and cyberattacks) where images and videos serve as critical evidence, forensic technologies that help to determine the origin, authenticity, and integrity of multimedia content can become essential tools. This book aims to collect a diverse and complementary set of articles that demonstrate new developments and applications in image and video forensics to tackle new and serious challenges to ensure media authenticity

    Advances in knowledge discovery and data mining Part II

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    19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II</p
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