The Combination of Artificial Intelligence and Extended Reality: A Systematic Review

Abstract

Artificial intelligence (AI) and extended reality (XR) differ in their origin and primary objectives. However, their combination is emerging as a powerful tool for addressing prominent AI and XR challenges and opportunities for cross-development. To investigate the AI-XR combination, we mapped and analyzed published articles through a multi-stage screening strategy. We identified the main applications of the AI-XR combination, including autonomous cars, robotics, military, medical training, cancer diagnosis, entertainment, and gaming applications, advanced visualization methods, smart homes, affective computing, and driver education and training. In addition, we found that the primary motivation for developing the AI-XR applications include 1) training AI, 2) conferring intelligence on XR, and 3) interpreting XR- generated data. Finally, our results highlight the advancements and future perspectives of the AI-XR combination.

The strategies for innovating with virtual reality and artificial intelligence: a literature review

“…However, these authors structured them from a technical perspective and identified technical challenges to overcome. In another publication [16], the results were structured from the use case perspective, describing scenarios in which VR/AI was reportedly technically successful with limited focus on technical challenges or market adaptivity potential. More philosophical studies were identified, envisioning the digitalisation of entire cities or societies [17].…”

“…We found that the most famous intersection of AI/VR domains was in medicine, with 37% of all articles included in a systematic literature review relating to this topic [16]. The most common application was incorporating machine learning models in medical training, primarily surgical.…”

Bi̇li̇şi̇m Si̇stemleri̇ Araştirma Alanindaki̇ Geni̇şleti̇lmi̇ş Gerçekli̇k Yayinlarinin Meti̇n Madenci̇li̇ği̇ Ve Doğal Di̇l İşleme (Nlp) Tekni̇kleri̇ Yoluyla Anali̇zi̇

“…Extended reality and machine learning are two distinct study areas, and their applications and focuses are different. Extended reality tries to extend people's capacities and experiences through computer generated environments whereas machine and deep learning are involved in information processing through the way of replication humans [30]. However, combination of those study areas generates new opportunities.…”

“…Extended reality serves artificial intelligence systems When the literature is examined, it is seen that sometimes extended reality technologies serve for artificial intelligence systems and sometimes artificial intelligence technologies serve for extended reality systems. Extended reality applications can become more useful and valuable through artificial intelligence because it makes communication easier by facilitating XR software to track things like gestures and eye movements, thus XR environment become more immerse as well as it makes [30,31]. In other respects, extended reality helps artificial intelligence systems by (1) facilitating their performance (2) training machine/ deep learning data without data comes from physical world, (3) simulate novel cases for training [30].…”

“…Extended reality applications can become more useful and valuable through artificial intelligence because it makes communication easier by facilitating XR software to track things like gestures and eye movements, thus XR environment become more immerse as well as it makes [30,31]. In other respects, extended reality helps artificial intelligence systems by (1) facilitating their performance (2) training machine/ deep learning data without data comes from physical world, (3) simulate novel cases for training [30].…”