Revolutionizing Archaeological Discoveries: The Role of Artificial Intelligence and Machine Learning in Site Analysis

Artificial Intelligence (AI) and Machine Learning (ML) utilization during the study of archaeological sites is a sea change in archaeology. The resulting possibilities of unlocking new features without the limits of traditional methods and improving the efficiency, precision, and breadth of archaeological research are at hand. The research follows this up with a look at how artificial intelligence (AI) and especially machine learning (ML) technology could detect and analyze archaeological sites and artefacts. It uses sophisticated algorithms such as Convolutional Neural Networks (CNN), LIDAR, & Ground-Penetrating Radar (GPR). We implement these cutting-edge technologies in remote scanning, scene modelling, and artefact classification. The second-best result in accuracy by the Artifact Classifier based on the CNN classifier was around $92 \%$. It demonstrated a precision rate of 88 % and an F1-score of $89 \%$, pointing out the high degree to which the device identified the artefacts. These models demonstrated astonishing $87 \%$ and $90 \%$ accuracy utilizing LIDAR detection and GPR analysis. These results showed again that these models are of great use when locating the site and analyzing the subsurface. As well as acknowledging the success achieved, the report highlights challenges when implementing new technologies in traditional archaeology procedures. Other barriers are ethical problems created by the protection of personal data, the possibility of bias, and the technological and cultural factors that prevent the rapid dissemination of biotechnology. The success of the AI and ML systems has demonstrated great potential for these technologies to transform the archaeological field. Nevertheless, applying these technologies should be done carefully and with the purpose of their improvement, discussing how to mitigate the risks and make them more beneficial. This research improves the subject with focused discussions on AI’s key consequences. It sets realistic challenges for AI in archaeology to offer an unbiased point of view on AI’s future use and development.