  This comprehensive review paper provides a thorough examination of current
advancements and research in the field of arc fault detection for electrical
distribution systems. The increasing demand for electricity, coupled with the
increasing utilization of renewable energy sources, has necessitated vigilance
in safeguarding electrical distribution systems against arc faults. Such faults
could lead to catastrophic accidents, including fires, equipment damage, loss
of human life, and other critical issues. To mitigate these risks, this review
article focuses on the identification and early detection of arc faults, with a
particular emphasis on the vital role of artificial intelligence (AI) in the
detection and prediction of arc faults. The paper explores a wide range of
methodologies for arc fault detection and highlights the superior performance
of AI-based methods in accurately identifying arc faults when compared to other
approaches. A thorough evaluation of existing methodologies is conducted by
categorizing them into distinct groups, which provides a structured framework
for understanding the current state of arc fault detection techniques. This
categorization serves as a foundation for identifying the existing constraints
and future research avenues in the domain of arc fault detection for electrical
distribution systems. This review paper provides the state of the art in arc
fault detection, aiming to enhance safety and reliability in electrical
distribution systems and guide future research efforts.
