Recognition of the Counterfeit Arduino Nano

Counterfeit Arduino chips pose a significant threat to educational environments, potentially leading to unreliable and unsafe results. This paper explores practical methods for detecting counterfeit chips, focusing on techniques accessible to educators. Visual inspection, including examination of chip markings and overall quality, is a simple yet effective method. Additionally, software tools can be employed to read the chip’s unique signature and compare it with known authentic values. While these methods offer valuable insights, they may not be foolproof against sophisticated counterfeiters. Future research should explore advanced techniques, such as machine learning and blockchain-based solutions, to enhance counterfeit detection capabilities.