K Yeshwanth

HKBK College of Engineering

Papers

1

Total Citations

3

H-Index

1

About

K Yeshwanth is a researcher at the forefront of applying artificial intelligence and the Internet of Things to critical infrastructure safety, with a particular focus on railway systems. Their most notable work introduces an advanced IoT and machine learning framework for railway safety, featuring a pioneering "Railway Track Tracer" technology that uses computer vision to autonomously detect cracks in railway tracks. By equipping trains with cameras and real-time ML analysis, Yeshwanth’s solution enables continuous, automated track inspection, replacing slower manual checks and offering a proactive method to prevent derailments and accidents. This contribution, already cited 3 times in its 2024 publication, demonstrates significant early impact in the field of intelligent transportation and predictive maintenance. Yeshwanth’s research bridges the gap between embedded systems and deep learning, offering a scalable, cost-effective approach to enhancing rail safety. Their work is particularly valuable for students and engineers interested in real-world applications of AI for public safety, showcasing how sensor data and machine learning can be combined to solve life-critical problems in legacy infrastructure.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Advanced IoT and Machine Learning Solutions for Railway Safety
3 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: HKBK College of Engineering

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago