374 research outputs found

    Location tracking in indoor and outdoor environments based on the viterbi principle

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    Integrating Smartdust into Intelligent Transportation System

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    The last few years have seen the emergence of many new technologies that can potentially have major impacts on Intelligent Transportation Systems (ITS). One of these technologies is a micro-electromechanical device called smartdust. A smartdust device (or a mote) is typically composed of a processing unit, some memory, and a radio chip, which allows it to communicate wirelessly with other motes within range. These motes can also be augmented with additional sensors – such as those for detecting light, temperature and acceleration – hence enhancing their features and making their application areas virtually limitless. As the smartdust concept is still relatively new, and very little is known about its application in transport domain, conducting research in this area may prove to be very valuable. It is generally perceived that smartdust will become the low-cost, ubiquitous sensor of the future, especially once its size shrinks dramatically to merit its name. Our involvement in several transport-related EU and UK funded projects (ASTRA, 2005; ASK-IT, 2007; EMMA, 2007; Foot-LITE, 2007; MESSAGE, 2007; TRACKSS, 2007) provides us with an opportunity to carry out experiments and to develop demonstrations of smartdust applications in transport systems. We also have a chance to investigate how smartdust can be used in collaboration with other (more traditional) transport sensors for developing better Co-operative Transport Systems (CTS). This paper outlines our experience in these projects and provides an illustration on the important role that the smartdust technology can play in future ITS. We also present encouraging results obtained from our experiments in investigating the feasibility of utilising smartdust in real ITS applications

    Indoor Localization for Fire Safety : A brief overview of fundamentals, needs and requirements and applications

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    An indoor localization system for positioning evacuating people can be anticipated to increase the chances of a safe evacuation and effective rescue intervention in case of a tunnel fire. Such a system may utilize prevalent wireless technologies, e.g., Bluetooth, RFID and Wi-Fi, which today are used to survey incoming and outgoing traffic to a certain space or location, to estimate group sizes and to measure the duration of visits during normal operation of buildings. Examples also exist of where the same wireless technologies are used for safety purposes, for example to assess real-time location, tracking and monitoring of vehicles, personnel and equipment in mining environments. However, they are relatively few, and typically rely on a high degree of control over the people that are to be tracked, and their association with (connection to) the localization system used for the tracking. In this report, the results of a brief overview of the literature within the field of indoor localization in general, and the application of indoor localization systems within the field of particularly fire safety, is summarized. This information forms the underlying basis for the planning and execution of a future field study, in which an indoor Wi-Fi localization system will be tested and evaluated in terms of if, and if so how, it can be used to position evacuating people in tunnels. Whereas such a system allows digital footprints to be collected within a wireless network infrastructure (also already existing ones), questions remains to be answered regarding aspects such as precision and accuracy, and furthermore, how these aspects are affected by other independent variables. In the end of this report, examples of research questions deemed necessary to answer in order to enable a sound evaluation of the system is presented. These need to be addressed in the future planning of the above-mentioned field study

    Evaluating the performance of absolute RSSI positioning algorithm-based microzoning and RFID in construction materials tracking

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    High accuracy of construction materials tracking with radio frequency identification technology (RFID) is challenging to achieve. The microzoning method consists essentially of an absolute received signal strength indication (RSSI) positioning algorithm on the basis of measuring the distance of tag from antennas base. In this paper, we analyse and examine the effects of microzoning method on the performance of RFID tags. A system was set up whereby RFID tags and antennas with the microzoning method were developed and studied. The performance of the tag antennas was studied with the practical read-range measurements. The study results showed that this absolute algorithm worked reliably and was suitable for RFID applications requiring identification of positions of onsite materials and components. The results also showed that the algorithm achieved a large read range and high accuracy. The study investigates the RFID solutions for Australian LNG (liquefied natural gas) industry and was initiated by the collaboration between Woodside Energy, Curtin University, and Industrial Automation Group Pty Ltd

    GNSS-free outdoor localization techniques for resource-constrained IoT architectures : a literature review

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    Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/

    Situational Awareness Enhancement for Connected and Automated Vehicle Systems

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    Recent developments in the area of Connected and Automated Vehicles (CAVs) have boosted the interest in Intelligent Transportation Systems (ITSs). While ITS is intended to resolve and mitigate serious traffic issues such as passenger and pedestrian fatalities, accidents, and traffic congestion; these goals are only achievable by vehicles that are fully aware of their situation and surroundings in real-time. Therefore, connected and automated vehicle systems heavily rely on communication technologies to create a real-time map of their surrounding environment and extend their range of situational awareness. In this dissertation, we propose novel approaches to enhance situational awareness, its applications, and effective sharing of information among vehicles.;The communication technology for CAVs is known as vehicle-to-everything (V2x) communication, in which vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) have been targeted for the first round of deployment based on dedicated short-range communication (DSRC) devices for vehicles and road-side transportation infrastructures. Wireless communication among these entities creates self-organizing networks, known as Vehicular Ad-hoc Networks (VANETs). Due to the mobile, rapidly changing, and intrinsically error-prone nature of VANETs, traditional network architectures are generally unsatisfactory to address VANETs fundamental performance requirements. Therefore, we first investigate imperfections of the vehicular communication channel and propose a new modeling scheme for large-scale and small-scale components of the communication channel in dense vehicular networks. Subsequently, we introduce an innovative method for a joint modeling of the situational awareness and networking components of CAVs in a single framework. Based on these two models, we propose a novel network-aware broadcast protocol for fast broadcasting of information over multiple hops to extend the range of situational awareness. Afterward, motivated by the most common and injury-prone pedestrian crash scenarios, we extend our work by proposing an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection for vulnerable road users. Finally, as humans are the most spontaneous and influential entity for transportation systems, we design a learning-based driver behavior model and integrate it into our situational awareness component. Consequently, higher accuracy of situational awareness and overall system performance are achieved by exchange of more useful information

    Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

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    The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

    Context-Aware Mobile Apps using iBeacons: Towards Smarter Interactions

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    In this paper we describe four mobile apps for iOS devices that use Bluetooth Low Energy iBeacons to provide contextual relevance and personalized experiences for the user. The applications span a number of vertical markets including asset tracking, food transportation logistics and health care. We developed these apps in collaboration with an industry partner located in Mississauga, Ontario, Canada. In this paper we present the relevant background of work in this area, the architectural framework that we designed and developed to support these context-aware apps, the apps themselves, and report on the findings of real use test case scenarios
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