Thermal-Aware Functional Safety Architecture for Automotive LED Drivers An AI–Cloud ML and NLP–Augmented Framework with Cybersecurity, Fraud Detection, and Disease Analytics
DOI:
https://doi.org/10.15662/IJARCST.2025.0806018Keywords:
thermal-aware functional safety, automotive LED drivers, AI–cloud machine learning, natural language processing, predictive diagnostics, cybersecurity, intrusion detection, fraud detection analytics, disease analytics, safety architecture, anomaly detection, smart vehiclesAbstract
The rapid evolution of automotive lighting systems has increased the demand for intelligent LED driver architectures that ensure high reliability, safety, and operational resilience. This paper presents a Thermal-Aware Functional Safety Architecture for Automotive LED Drivers, augmented with AI–Cloud machine learning (ML) and natural language processing (NLP) to enhance predictive diagnostics and system transparency. The proposed framework integrates real-time thermal monitoring, fault prediction, and safety state transitioning to mitigate overheating risks and functional degradation in high-intensity LED modules. Cloud-based ML models provide multivariate analysis for anomaly detection, while NLP-driven interfaces enable automated reporting, event interpretation, and human-readable safety recommendations.To strengthen system robustness, the architecture embeds cybersecurity controls, including secure communication channels, anomaly-driven intrusion detection, and access-controlled firmware updates. Additionally, the framework incorporates fraud detection analytics to protect connected automotive billing, warranty, and supply-chain data. A cross-domain disease analytics module is introduced to support driver health monitoring and vehicle–occupant safety correlations in next-generation smart vehicles. The unified architecture demonstrates improved thermal stability, reduced failure probabilities, enhanced cyber protection, and comprehensive multi-modal analytics capabilities. This work contributes a scalable, AI-driven, and functionally safe LED driver ecosystem for intelligent automotive platforms.
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