Coastal erosion in Mauritius is increasing due to climate change and human activities. Traditional shoreline monitoring methods lack accessibility, affordability, and accuracy, prompting the need for more innovative approaches. This study introduces a novel method that combines drone technology and easily integrable Artificial Intelligence to monitor beach erosion, providing an accessible, cost effective, and precise solution. This study addresses a notable research gap by proposing a comprehensive and replicable methodology for drone-based shoreline monitoring and erosion analysis which encompasses site selection criteria, optimized flight planning for data acquisition, data management, and image preprocessing techniques. Our proposal has been tested for the endangered coastline of Mauritius, creating the island’s first comprehensive erosion dataset and demonstrating the effectiveness of the proposed approach. We present the details of the drone operation, image capture, and data processing steps to provide a clear foundation for practical application and future research. This study not only advances local erosion monitoring efforts but also sets a new standard in the field, advocating for the widespread adoption of drone technology in environmental monitoring to support sustainable coastal management worldwide.