Recently, I co-authored an open-access journal paper that was published at IEEE Access. The paper is entitled “An Augmented Reality System With an Offline LSTM-Based Fault Recognition Model for Sewer Pipeline Inspection”. The paper introduces XR5.0, a novel framework that combines artificial intelligence with extended reality (XR) technologies to support the vision of Industry 5.0, where advanced digital systems are designed around human needs and capabilities. The research proposes a human-centric XR paradigm that integrates immersive environments with AI to enhance collaboration between workers and intelligent machines.
A key component of the approach is the use of human-centred digital twins, which create digital representations of users to enable XR systems to adapt training, guidance, and information delivery according to individual skills, context, and tasks. The framework also integrates advanced AI techniques (including explainable AI, generative AI, active learning, and neurosymbolic AI) to provide real-time decision support and personalized learning within immersive environments. These capabilities enable practical applications such as industrial training, remote maintenance, assembly guidance, and product design simulations.
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