AUGMENTED REALITY AND IOT-DRIVEN TELEMETRY: ENHANCING DECISION-MAKING AND ENERGY EFFICIENCY IN HIGH-PERFORMANCE AND ELECTRIC VEHICLE SYSTEMS
Keywords:
Augmented Reality, Electric Vehicles, IoT Telemetry, Energy Recovery SystemsAbstract
Introduction: The automotive industry is currently undergoing a radical transformation driven by stringent environmental regulations, such as EU Regulation 2023/851, and the rapid evolution of connected technologies. As vehicles transition from mechanical systems to software-defined platforms, the volume of telemetry data generated presents a cognitive challenge for operators and engineers.
Methods: This study investigates the integration of Augmented Reality (AR) situated visualization with Internet of Things (IoT) telemetry to enhance decision-making processes in high-performance and solar-powered electric vehicles. Drawing on methodologies from Formula 1 engineering—specifically active suspension and energy recovery systems—we utilized a combination of Computational Fluid Dynamics (CFD) simulations for aerodynamic efficiency and acoustic analysis for gearbox performance. These physical datasets were then piped into a novel AR interface designed to visualize real-time performance metrics.
Results: Our analysis reveals that situated AR visualization significantly reduces the cognitive load required to interpret complex datasets, such as underbody battery aerodynamics and gearbox vibration profiles. Furthermore, the application of optimal control theories derived from motorsport demonstrated a theoretical improvement in energy recovery efficiency when coupled with predictive visualization tools.
Conclusion: The convergence of AR, IoT, and advanced automotive engineering offers a viable pathway for managing the complexity of modern electric vehicles. However, this data-rich environment necessitates a robust approach to privacy and algorithmic transparency, paralleling concerns found in medical AI and educational data mining.
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