35,225 research outputs found

    A novel context-aware augmented reality framework for maintenance systems

    Get PDF
    Augmented Reality (AR) bridges the gap between the real and the virtual world by bringing virtual information to a real environment as seamlessly as possible. The need for better perception of knowledge-intensive complex maintenance tasks and access to large amounts of documents and data makes the use of AR technology promising in a maintenance domain. Context-awareness enhances the usability of such AR applications, i.e. the output and behavior of the system will be adapted according to different contexts, such as the user location, preferences, devices, etc. to afford a higher level of personalization. The adaptation needs to be efficient in terms of performance and speed. This paper presents an optimized framework which combines context-awareness and AR for training and assisting technicians in maintaining equipment in an industrial context to improve field workers effectiveness. Ontology is used to model a maintenance context, and Semantic Web Rule Language (SWRL) provides logical reasoning. This optimized framework utilizes a behavior network to select a collection of suitable actions based on the current step of an ongoing task, and applies context-based inferred information from the ontology to each member of this collection. Evaluation results comparing the performance of the proposed framework with conventional ontology alone in a maintenance domain confirmed that the proposed framework in this research provides the same results as the ontology in terms of content, but it runs much faster in terms of run-time and performance. The proposed context-aware framework is quite valuable especially in terms of response time and performance for maintenance systems with a large number of maintenance activities

    Continuous maintenance and the future – Foundations and technological challenges

    Get PDF
    High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

    Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

    Get PDF
    The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

    Pervasive Displays Research: What's Next?

    Get PDF
    Reports on the 7th ACM International Symposium on Pervasive Displays that took place from June 6-8 in Munich, Germany

    Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns

    Get PDF
    We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their proximal environment. Our approach uses a low-cost mobile thermal camera integrated into a smartphone to capture thermal textures. A deep neural network classifies these textures into material types. This approach works effectively without the need for ambient light sources or direct contact with materials. Furthermore, the use of a deep learning network removes the need to handcraft the set of features for different materials. We evaluated the performance of the system by training it to recognise 32 material types in both indoor and outdoor environments. Our approach produced recognition accuracies above 98% in 14,860 images of 15 indoor materials and above 89% in 26,584 images of 17 outdoor materials. We conclude by discussing its potentials for real-time use in HCI applications and future directions.Comment: Proceedings of the 2018 CHI Conference on Human Factors in Computing System

    Is Ambient Intelligence a truly Human-Centric Paradigm in Industry? Current Research and Application Scenario

    Get PDF
    The use of pervasive networked devices is nowadays a reality in the service sector. It impacts almost all aspects of our daily lives, although most times we are not aware of its influence. This is a fundamental characteristic of the concept of Ambient Intelligence (AmI). Ambient Intelligence aims to change the form of human-computer interaction, focusing on the user needs so they can interact in a more seamless way, with emphasis on greater user-friendliness. The idea of recognizing people and their context situation is not new and has been successfully applied with limitations, for instance, in the health and military sectors. However its appearance in the manufacturing industry has been elusive. Could the concept of AmI turn the current shop floor into a truly human centric environment enabling comprehensive reaction to human presence and action? In this article an AmI scenario is presented and detailed with applications in human’s integrity and safety.Ambient Intelligence, networks, human-computer interaction
    corecore