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Dr. Ahmed Awad | Control Engineering | Best Researcher Award

Senior Electrical Maintenance Engineer at SESCO TRANS Company, Egypt

Summary:

Dr. Ahmed Awad is an accomplished electrical and control systems engineer with a blend of academic achievements and practical engineering expertise. His work integrates advanced control system algorithms and IoT-driven solutions to enhance the operational efficiency of logistic equipment. Dr. Awad is committed to the seamless fusion of theoretical research and hands-on engineering practice, contributing to innovative advancements in industrial control technologies.

Professional Profile:

šŸ‘©ā€šŸŽ“Education:

Dr. Ahmed Awad has a robust academic foundation in Control Engineering. He completed his Bachelor’s degree at Banha University in 2013, graduating with honors and an impressive project on Building Automation Systems, where he led the team to achieve an “Excellent” grade. He proceeded to Mansoura University, obtaining a Preliminary Masterā€™s degree with a grade of ā€œVery Goodā€ in 2014, followed by a Master’s degree in Computer & Automatic Control Engineering in 2018. Dr. Awad is currently registered for his Ph.D. at Mansoura University as of July 2020, continuing his pursuit of advanced research in his field.

šŸ¢ Professional Experience:

With over eight years of extensive experience, Dr. Awad has served as a Senior Electrical Maintenance Engineer at Sesco Trans for Developed Logistics since May 2015. In this role, he has expertly managed the maintenance, troubleshooting, and repair of various logistics heavy equipment, including mobile harbor cranes, loaders, excavators, forklifts, and trucks. His work encompasses designing and maintaining control circuits, programming PLCs (Simatic S5/S7, LS Master K), and handling motor drives such as Siemens SIMOREG and Parker SSD drives. Dr. Awad’s proficiency extends to installing, commissioning, and repairing electronic circuit boards, as well as training new engineers in electrical concepts and maintaining foundational knowledge in hydraulics and mechanical systems.

Research Interests:

Dr. Awad’s research centers on enhancing automation and control systems with a focus on applying algorithms for performance optimization. He has a keen interest in integrating IoT frameworks and deep learning methodologies for monitoring and controlling industrial systems, particularly in the context of logistics and heavy equipment. His work also delves into algorithm-based motor control systems and quality control for logistics applications.

Author Metrics:

Dr. Awad’s publications have been recognized for their relevance in the engineering and computer science communities, contributing to discussions on motor control algorithms, IoT applications, and logistics automation solutions.

Top Noted Publication:

Enhancing Tracking Performance Parameters of Induction Motor Based on PI-PSO Algorithm

  • Authors: M. M. Abd-Elsalam, M. S. Elkasas, S. F. Saraya, A. H. Awad
  • Journal: International Journal of Scientific & Engineering Research
  • Year: 2017
  • Summary: This research investigates the performance improvement of induction motors using a Proportional-Integral (PI) controller optimized with a Particle Swarm Optimization (PSO) algorithm. The study addresses the limitations of conventional PI controllers and demonstrates how integrating PSO enhances the dynamic performance of induction motors, focusing on improved tracking parameters and reduced steady-state error.

IoT Based Framework for Monitoring and Controlling Movable Harbor Cranes

  • Authors: A. H. Awad, M. S. Saraya, M. S. M. Elksasy, Amr M. T. Ali-Eldin
  • Conference: 2021 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), IEEE
  • Year: 2021
  • Summary: This paper presents an Internet of Things (IoT) framework designed for the real-time monitoring and control of movable harbor cranes. The system aims to enhance operational efficiency and reduce human intervention by utilizing IoT-based sensors and controllers. The proposed framework demonstrates improvements in data collection, crane performance, and remote control capabilities.

A Quality Control System for Logistic Ports Goods Movable Harbor Cranes Based on IoT and Deep Learning

  • Authors: A. H. Awad, M. S. Saraya, M. S. M. Elksasy, Amr M. T. Ali-Eldin, M. M. Abd-Elsalam
  • Journal: Indonesian Journal of Electrical Engineering and Computer Science
  • Year: 2024
  • Summary: This study develops a quality control system for logistics ports, focusing on the operation of movable harbor cranes. The system leverages IoT technology combined with deep learning algorithms to monitor and ensure the safe and efficient handling of goods. The approach enhances fault detection and predictive maintenance, contributing to a more reliable and automated port management system.

Conclusion:

Dr. Ahmed Awadā€™s unique combination of practical engineering expertise and applied research in control systems and IoT positions him as a strong candidate for the Best Researcher Award. His work on optimizing control algorithms and integrating deep learning for enhanced system performance demonstrates significant potential for continued contributions to the field. To maximize his impact, expanding his research collaborations and publication reach would further cement his status as a leader in control engineering. Overall, Dr. Awad exemplifies the qualities of a dedicated researcher who merges innovation with real-world engineering challenges.

 

Ahmed Awad | Control Engineering | Best Researcher Award

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