FLOW VR: A Review of Motion Tracking, Gesture-Based Interaction, and AI-Driven Interfaces in Low-Cost Mobile Virtual Reality Systems

Affordable smartphone-based virtual reality (VR) offers a practical route to immersive computing for users who cannot access dedicated head-mounted displays. However, an effective mobile VR experience depends on the coordinated operation of motion tracking, hand interaction, artificial-intelligence (AI) planning, and voice-based interfaces within limited processing, battery, thermal, and privacy budgets. This paper reviews these technical areas as connected components of a low-cost mobile VR platform rather than as independent research topics. The review considers inertial measurement unit (IMU) sensor fusion for head orientation; camera-based hand landmark detection and gesture recognition; interaction design for hands-free use; classical search and planning algorithms for interactive environments; and natural language processing (NLP) pipelines for conversational assistance. The literature search covered IEEE Xplore, ACM Digital Library, ScienceDirect, SpringerLink, Scopus, Web of Science, and arXiv, prioritizing peer-reviewed work from 2015 onward while retaining earlier foundational methods where appropriate. The synthesis indicates that complementary, Kalman-family, Madgwick, and Mahony filters offer different accuracy–complexity trade-offs; learned hand-landmark detectors combined with lightweight geometric rules are well suited to mobile inference; and algorithms such as A* and alpha–beta pruning require bounded or scheduled computation for interactive use. NLP components can support voice-driven access, but latency and headset-mediated input constraints remain important. The review identifies a systems-level research gap: these subsystems are commonly studied separately, while integrated mobile VR must resolve shared compute budgets, multimodal arbitration, usability, cybersickness, and camera privacy together. The paper concludes with design considerations and research directions for accessible, reliable, and resource-aware mobile VR.