A smart exception handler system for safety-critical real-time systems is provided. The system is configured to: receive a plurality of parameters at a plurality of nodal points in a real-time execution path; analyze the received parameters using a trained exception handling model, wherein the trained exception handling model has been trained using machine learning techniques to learn the critical path of execution and/or critical range of parameters at critical nodes, wherein the critical range of parameters comprises a learned threshold at a node; compute, using the trained exception handling model, a probability of fault at the critical nodes; compare the probability of fault at a critical node against a learned threshold at the node; and take proactive action in real-time to avoid the occurrence of a fault when the probability of fault at the node is higher than the learned threshold at the node.
AUGMENTED EXCEPTION PROGNOSIS AND MANAGEMENT IN REAL TIME SAFETY CRITICAL EMBEDDED APPLICATIONS
ERWEITERTE AUSNAHMEPROGNOSE UND VERWALTUNG IN ECHTZEIT IN SICHERHEITSKRITISCHEN EINGEBETTETEN ANWENDUNGEN
PRONOSTIC ET GESTION AMÉLIORÉS DES EXCEPTIONS DANS LES APPLICATIONS EMBARQUÉES CRITIQUES POUR LA SÉCURITÉ EN TEMPS RÉEL
2020-09-30
Patent
Electronic Resource
English
Augmented exception prognosis and management in real time safety critical embedded applications
European Patent Office | 2022
|AUGMENTED EXCEPTION PROGNOSIS AND MANAGEMENT IN REAL TIME SAFETY CRITICAL EMBEDDED APPLICATIONS
European Patent Office | 2020
|A statistical approach for real-time prognosis of safety-critical vehicle systems
Automotive engineering | 2007
|A Statistical Approach for Real-Time Prognosis of Safety-Critical Vehicle Systems
British Library Conference Proceedings | 2007
|A Statistical Approach for Real-Time Prognosis of Safety-Critical Vehicle Systems
SAE Technical Papers | 2007
|