M Elshaikh
Papers
1
Total Citations
2
H-Index
1
About
M. Elshaikh’s research lies at the intersection of industrial automation, computer vision, and the Internet of Things (IoT), with a focus on enhancing robotic material handling systems. Their most-cited work, “Development of Vision Based Smart Gripper for Material Handling Using Internet of Things” (2022), addresses a critical challenge in modern manufacturing: enabling robotic grippers to intelligently perceive and adapt to objects in real time. By integrating vision sensors with IoT connectivity, Elshaikh’s design allows grippers to autonomously identify, locate, and grasp items—reducing reliance on pre-programmed routines and improving flexibility in dynamic production lines. This contribution is particularly relevant to the growing demand for smart factories and Industry 4.0 solutions. While their citation count is still emerging, the work has garnered attention for its practical approach to overcoming common obstacles in vision-based automation, such as lighting variability and object diversity. Elshaikh’s research offers a promising pathway toward more adaptive, efficient, and cost-effective material handling, making it a valuable reference for engineers and researchers exploring the convergence of robotics, computer vision, and IoT in industrial settings.
Research Focus
Key Achievements
Top Papers
- 1