Renu Popli
Papers
2
Total Citations
41
H-Index
2
About
Dr. Renu Popli is a leading researcher at the intersection of the Internet of Things (IoT), fog computing, and robotics, with a strong focus on developing intelligent systems for real-world challenges. Her major contributions lie in creating robust, deep learning-enabled robotic vision systems for critical applications in agriculture and infrastructure. Notably, her work on "IoT-Fog-enabled robotics-based robust classification of hazy and normal season agricultural images for weed detection" (26 citations) pioneers the use of fog computing to enhance robotic weed detection in challenging visual conditions, directly advancing precision agriculture. Complementing this, her research on "ROAD: Robotics-Assisted Onsite Data Collection and Deep Learning Enabled Robotic Vision System for Identification of Cracks on Diverse Surfaces" (15 citations) introduces a novel, automated approach for infrastructure safety, using robotics and deep learning to identify cracks on roads and other surfaces with high accuracy. These contributions demonstrate Dr. Popli’s ability to integrate cutting-edge technologies—IoT, fog, and robotics—to solve pressing problems in food security and public safety, marking her as an influential voice in the field of applied intelligent systems.
Research Focus
Key Achievements
Top Papers
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