Table of Content

Futuristic Evolutionary Intelligence Algorithms and Models for Augmented and Virtual Reality Applications

Submission Deadline: 03 February 2022 (closed)

Guest Editors

Dr. Deepa Jose, KCG College of Technology, India.
Dr. M. Suchetha, Vellore Institute of Technology, India.
Dr. R. Vani, SRM Institute of Science and Technology, India.
Dr. Pancham Shukla, Imperial College London, UK.


The growth of Augmented Reality and Virtial Reality (AR/VR) is digital media that allows the user to integrate virtual context into the physical environment in an interactive multidimensional way have grown exceptionally. AR derives information about the surrounding environment from cameras and sensors. Implementing AI platform that use the most advanced evolutionary algorithms to reduce the search space along with deep learning and distributed computation technology enhances the AR/VR experience to tackle complex problems including NP Hard Problems and derive meaningful results. This helps in implementing decision models for AR and VR which will have far reaching improvements in the performance of the entire system. Together, Augmented Reality, AI, and Virtual Reality can be the three cardinals of the future technology.

AR/ VR technology is used for smart cities, Industry 4.0, education, construction, weapon aiming, space explorations, human machine interactions, self driving cars, navigation systems, architecture, design, safety and inspection, Underground constructions,Weapon aiming and telepresence in military operations, gaming systems, Internet of Things, and smartphone technology. Though applications are wide ranging effective algorithms and systems still does not exist for AR/VR models. Evolutionary intelligent algorithms is the future of engineering and there is a demand to explore and identify new hybrid models and new methods that can offer reassuring solutions for next generation AR/VR systems and applications. In robotics, AR and evolutionary intelligence acts as a new medium for interaction and information exchange with autonomous systems increasing the efficiency of the human-robot interaction (HRI). Virtual Reality can be used to develop teleoperating robots that can function with the help of multiple sensor displays. This special issue will cover novel algorithm models and use-cases related to augmented evolutionary intelligence algorithms that empower AR/VR systems to resolve complex optimization problems.


• Deep Learning Models and Evolutionary Algorithms for AR /VR in Health Care
• Evolutionary and AI based optimization techniques for AR/VR
• Power efficient Hybrid algorithms for AR/VR
• Fault Aware and Reliable Evolutionary AI algorithms for AR/VR
• Computer vision approaches based on Evolutionary AI for AR/VR
• Bio- Inspired Optimization Models and Systems for Object Detection, Text Analysis, and Scene Labeling
• Evolutionary Intelligence for VR/AR Controllers
• Data Analytics and Multiple Sensor Interface for AR/VR
• Algorithms and Systems for Robotic automation using Evoltutionary Intelligence
• AR/VR based Vehicle Perception Solutions using Evolutionary AI
• AR and AI based Navigation Systems

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