Digital twin technology has emerged as a foundation for modern hybrid engineering, integrating physical assets with their virtual replicas through continuous, automated bidirectional data synchronisation. This paper explores the concepts, technologies, applications, challenges and future directions of digital twin technology.

Explainability is a significant weakness of artificial intelligence. While modern AI delivers outstanding performance, its black box creates significant trust and safety difficulties for users. This paper provides an overview of explainable AI (XAI), a field dedicated to making AI decisions more transparent and interpretable.

This paper seeks to explore the history of artificial intelligence (AI) and explainable AI (XAI), including its recent role in a multitude of disciplines, such as healthcare, finance and law. The paper seeks to explore both the advantages and disadvantages of deploying XAI in the concerned fields and to visualise its use in the future.

This article examines the trajectory and design principles of artificial intelligence enabled robots that form a context of human-robot interaction, as well as their social effects, ethical considerations and future implications.

Robots have evolved from industrial machines designed to perform hazardous, repetitive tasks to social companions capable of interacting with and assisting humans in healthcare, education and daily life. This paper examines the use of social robots across core industries, identifies challenges in implementation and offers potential solutions.