Kamya Brata Debnath

About

Kamya Brata Debnath is a researcher focused on intelligent transportation systems and embedded AI safety solutions. Their most-cited work, "Advanced Collision and Obstruction Detection and Prevention using ESP-32 & Deep Learning" (2023), addresses the critical challenge of road safety in increasingly congested environments. By integrating low-cost ESP-32 microcontrollers with deep learning algorithms, Debnath proposes a scalable framework for real-time collision and obstruction detection, bridging the gap between affordable hardware and sophisticated neural network models. This contribution offers a practical pathway for deploying advanced driver-assistance systems (ADAS) in resource-constrained settings, potentially reducing accident rates in complex traffic scenarios. With 2 citations, the paper has already sparked interest among researchers exploring edge computing and vehicular safety. Debnath’s work exemplifies a hands-on, interdisciplinary approach, combining embedded systems, computer vision, and machine learning to tackle pressing societal problems. Their research not only advances technical methodologies but also emphasizes accessibility, making high-impact safety technologies more viable for widespread adoption.

Research Focus

Key Achievements

Top Papers

1. 1
   Advanced Collision and Obstruction Detection and Prevention using ESP-32 & Deep Learning.

   2 citations · 2023

Key Collaborators

Contact & Links