DrivebuddyAI, an Ahmedabad-based developer of AI-powered driver assistance and fleet monitoring systems, has been granted a patent for an Integrated Dynamic Road Quality Assessment System. The technology autonomously detects and geo-tags road surface hazards — including potholes, rough patches, and deteriorated road sections — using a combination of onboard sensors and deep learning-based computer vision trained on Indian road conditions.
The system works by pulling data from two sources simultaneously. A GNSS sensor tracks vehicle speed and precise location, while an inertial measurement unit (IMU) monitors acceleration across three axes. A sudden spike in vertical (Z-axis) acceleration signals a potential road defect. The system then cross-references a video feed of the flagged location through a fine-tuned deep learning model, which visually confirms whether a genuine road defect is present — reducing false positives before logging a geo-tagged alert.
Unlike static road surveys, the platform continuously updates its road quality map as new data flows in from active fleet vehicles. The result is a live, crowd-sourced dataset of road conditions across fleet routes, rather than a periodic snapshot.
Nisarg Pandya, Founder and CEO of drivebuddyAI, said the patent addresses a blind spot in conventional navigation platforms, which optimize routes by time and distance but do not account for road surface quality. "Road quality is not a standalone problem; it sits at the intersection of driver safety, cargo protection, and fleet efficiency," Pandya said in a statement.
The gap has tangible consequences for fleet operations. Poor road conditions increase braking frequency, accelerate tyre and suspension wear, raise the risk of cargo damage, and force reactive driving — all of which eat into turnaround times that fleet operators are contractually measured against. A route that appears faster on a standard navigation app can become slower and more costly in practice if the road surface is in poor condition.
drivebuddyAI says its system allows dispatchers to weigh road quality alongside time and distance when assigning trips, potentially reducing maintenance costs and improving on-time delivery rates for time-critical or high-value cargo.
The patent adds to drivebuddyAI's portfolio of more than 15 patents spanning ADAS, driver monitoring, drowsiness detection, and driver risk assessment. The company says its systems are validated against Indian (AIS184), European (EU2144/2019 and 2023), and EURO NCAP 2026 standards.
drivebuddyAI is a group company of Roadzen Inc., a Nasdaq-listed company (RDZN) focused on AI applications in auto insurance. Its fleet technology customers span sectors including e-commerce logistics, chemical and hazardous materials transport, and passenger transportation.