Kholoud Shata

Egypt-Japan University of Science and Technology

Papers

Total Citations

H-Index

About

Kholoud Shata is a researcher focused on intelligent transportation systems and real-time accident detection technologies. Her most cited work, "Fast Fourier Transform based Method for Accident Detection" (2022), introduces a novel approach that leverages signal processing techniques to rapidly identify vehicular accidents, aiming to reduce emergency response times and save lives. This method offers a computationally efficient alternative to traditional hardware-dependent systems, highlighting her contribution to making accident detection more accessible and faster. With 2 citations, this paper demonstrates early impact in a critical area of road safety. Shata’s research addresses a pressing societal challenge—minimizing accident fatalities through technological innovation. Her work stands out for its potential to integrate into existing infrastructure without specialized equipment, promising broader deployment. As a researcher, she is contributing to the growing field of smart mobility, where data-driven solutions enhance public safety. Her achievements reflect a commitment to practical, life-saving applications of computational methods, positioning her as an emerging voice in transportation safety research.