How blockchain technology can boost Industry 4.0 robotic systems

   2021-11-24 10:11

Dr Saeed Hamood Alsamhi of Athlone IT is researching the feasibility of applying blockchain technology to robotic systems that can be used in fields ranging from smart manufacturing to disaster monitoring.

Dr. Saeed Hamood Alsamhi has traveled the world on a research journey that took him to the fields of blockchain and robotics. He earned a master’s degree and a PhD from the Indian Institute of Technology after starting his studies in engineering at the University of Eve in Yemen. After that, I went to China as a postdoctoral fellow at Tsinghua University and became an assistant professor at the Shenzhen Institute of Advanced Technology.

Alsamhi is currently a Marie Sklodowska-Curie Actions Fellow of Confirm, the Smart Manufacturing Research Center of the Irish Science Foundation, and is based in Athlone IT. His research interests include blockchain technology, multi-robot collaboration, digital twins, space technology, the Internet of Things, and green communication.

“Multi-robot systems have a wide range of application scenarios, especially in dangerous, unknown, or dangerous environments.” – DR SAEED HAMOOD ALSAMHI

What made you decide to become a researcher?

Growing up, I loved asking how advanced technology could improve our quality of life and make our world smarter and more environmentally friendly. My interest in research began when I received my master’s degree from the Indian Institute of Technology in Varanasi, India. This was my first time writing an article, and when I attended an international conference, many participants asked questions and thanked me for the ideas I proposed. This allowed me to do more research on advanced technologies and applications.

I got a PhD in space technology and continued my research. Before I got my PhD, I received a message from Professor OuMa of the Department of Aerospace Engineering at Tsinghua University in Beijing, China. He invited me to work with him as a postdoc in the field of optimal and smart wireless network research and its applications to enhance robotics technology. When I checked the rank of Tsinghua University, it was ranked 17th in the world. This news made my day beautiful.

Please tell us about the research you are currently working on.

My current research focuses on multi-robot collaboration to reach consensus during intra-industry or out-of-industry task performance with the help of blockchain technology. The project aims to develop a distributed ledger platform with corresponding algorithms to enable collaboration between network partitions and Byzantine robots, or heterogeneous robots with unreliable robot tolerances.

This project explores the constraints and characteristics of realistic robot collaboration applications and develops a consensus algorithm for robotics-oriented blockchain systems. The selected robot application will be implemented on top of the blockchain system. For example, the best of n problem, which is an abstraction of the discrete consensus achievement problem.

In your opinion, why is your research important?

All research work is important, but I think it’s important because I’m trying to use blockchain technology to explore realistic heterogeneous robot collaboration applications with decentralized, high security levels.

It helps manage heterogeneous multi-robots in Irish and EU smart factories, accomplish complex tasks effectively and efficiently, and increase productivity in ways not possible with a single robot. .. In addition, multi-robot collaboration is needed for disaster management to effectively respond to and mitigate potential adverse effects.

The robot can also be used to monitor and combat Covid-19 and future pandemics. Autonomous robot collaboration can deliver services, products and medicines anywhere. During Covid-19, the robot delivered objects to the quarantine area and performed tasks in the hospital without human intervention.

I have already published two articles in the journal on this point: Covid-19 and the blockchain for decentralized multi-drones to fight future pandemics: frameworks and proposed solutions, and Covid-19. Multi-robot collaboration utilizing blockchain to fight future pandemics.

What commercial applications do you anticipate for your research?

The development of distributed robot collaboration has the potential to accelerate the adoption of multi-robot systems in the industry. Smart manufacturing of multi-robot collaboration has several commercial applications such as object processing and transportation, natural resource monitoring, and delivery operations.

Commercial applications include disaster monitoring and management, emergency response and rescue, fault repair and diagnostics for outdoor industry operations. In addition, healthcare can use multi-robot collaboration to avoid human interactions and fight and monitor pandemics such as Covid-19.

Multi-robot systems have a wide range of application scenarios, including particularly dangerous, unknown, or dangerous environments, such as humanitarian demining, search and rescue, underwater exploration or surveillance.

What are the biggest challenges you face as a researcher in your field?

My current research is in the very early stages. The focus is to verify the feasibility of applying blockchain technology to robotic systems. So far, the results are good, but there are many challenges.

Most solutions require each robot to process transactions and save the state of the world. [a database that holds current values of a set of ledger states] Similarly, just like a normal blockchain system. However, these solutions are difficult to deal with capacity non-uniformity and network partitions.

What research field do you want to work on in the future?

With advances in communication technologies such as Beyond 5G and 6G integrated with blockchain and federated learning, multi-robot collaboration in Industry 4.0 solves real-world challenges and increases productivity process flexibility. You can improve the performance of decisions and actions and improve the actual response. time.

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