Bashir Salah
Papers
7
Total Citations
124
H-Index
5
About
Bashir Salah is a versatile engineering researcher whose work bridges precision agriculture, robotics, and intelligent automation systems. His research spans two compelling domains: agricultural robotics and automated storage and retrieval systems (AS/RS), with a growing emphasis on Industry 4.0 integration. Salah's most prominent contribution is the development of TobSet, a specialized image dataset for tobacco crop and weed classification, enabling agricultural robots to perform real-time selective spraying using convolutional neural networks — a paper that has garnered 34 citations since 2022 and addresses critical challenges in sustainable precision farming. His parallel body of work on wire-driven robotic storage systems has been equally influential; his 2012 study introducing a wire robot-based storage retrieval machine for high racks earned 29 citations, and subsequent publications refined this design using FMEA analysis and validated control architectures, collectively demonstrating a systematic approach to intralogistics innovation. His research on Stewart-Gough Platform travel time modeling further reflects his deep engagement with warehouse automation efficiency. More recently, Salah has extended his expertise toward smart manufacturing, contributing to real-time Industrial Revolution 4.0 implementations. With over 120 cumulative citations, his interdisciplinary contributions make him a meaningful voice across robotics, automation, and agri-technology research communities.
Research Focus
Key Achievements
Top Papers
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- 2Development of a Storage Retrieval Machine for High Racks Using a Wire Robot29 citations · 2012
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