drivebuddyAI Secures Patent for Revolutionary Driver Scoring Algorithm 'CARD'

drivebuddyAI announces a patent for its CARD algorithm, revolutionizing driver safety with AI, computer vision, and real-time vehicle monitoring. This innovative system assesses driver behavior and risk, enhancing fleet management by offering data-driven insights and proactive safety interventions, contributing significantly to reduced accident probabilities and optimized resource allocation.

drivebuddyAI, a pioneering force in AI-driven driver monitoring systems, proudly announced it has secured a patent for its novel driver scoring algorithm, denoted as CARD (Cognitive Assessment of Risk for Drivers). This innovative analytical framework redefines safety standards by utilizing AI, computer vision, and real-time vehicle monitoring to meticulously evaluate driver behavior and risk settings. The patent underscores a significant advancement in driver scoring, risk assessment, and incentivization methods paramount to fleet risk management.

According to Nisarg Pandya, CEO of drivebuddyAI, the CARD system integrates data from Advanced Driver Assistance Systems (ADAS) and Driver Monitoring Systems (DMS) embedded in vehicles. The sophisticated algorithm processes extensive contextual data, including driver compliance to in-cabin alerts issued by ADAS and DMS, history of behavioral coaching interventions, environmental considerations, and positive driving behaviors such as proactive alert responses. This comprehensive evaluation strategy empowers fleet managers with data-backed insights for making informed decisions about driver assignments, risk mitigation strategies, and overall fleet operational enhancements.

Rohan Malhotra, CEO of Roadzen, emphasized CARD's potential in aiding insurers, fleets, and logistics providers in accident prevention and risk assessment, marking a monumental leap in AI road safety. Meanwhile, Kanaksvi Pacholi, drivebuddyAI's Data Scientist, highlighted the fairness and reliability of the CARD framework, ensuring drivers are assessed equitably while identifying high-risk patterns and encouraging better driving habits through dynamic feedback mechanisms.

(With inputs from agencies.)