PromptAid Vision: AI-Assisted Crisis Image Interpretation Performance Evaluation and Expert-Reviewed Data Collection Platform

Crisis maps and drone imagery are widely produced during humanitarian emergencies, yet their interpretation requires expertise and time - resources that are scarce during response operations. This work presents PromptAid-Vision, a web-based platform that integrates vision–language models (VLMs) to support rapid interpretation of crisis maps and disaster imagery for emergency decision making.

The prototype includes four core functions: image upload, dataset exploration, analytics visualization, and an administration dashboard. It is designed to streamline expert data collection, evaluate VLM performance for humanitarian image interpretation, and enable future model fine-tuning. Experts can upload crisis images and receive VLM-generated descriptions, analyses, and recommended actions. They may edit these outputs, providing high-quality image-text pairs for future training. A built-in survey allows users to score VLM responses across three dimensions - accuracy, context, and usability.

The system currently integrates a range of commercially available VLMs and presents all collected data, user interactions, and model performance metrics through an analytics dashboard. An administrative interface supports model configuration and system-prompt management.

The work contributes: (1) the creation of an expert-reviewed dataset of crisis image-interpretation pairs, and (2) an evaluation framework for assessing VLM performance in humanitarian contexts. Next steps include public deployment for large-scale data collection and fine-tuning of VLMs for crisis-mapping applications.