"AI-Integrated Operational Dashboard for Hail Defense Operational Systems"

This study presents the design and implementation of a comprehensive Hail Operational Aircraft Information Dashboard system. This system, which aims at user-friendliness and a customizable visualization platform, is a helpful tool for enhancing decision-making and optimizing cloud seeding operations for hail suppression. It leverages real-time and historical data, making it accessible and easy to coordinate operations with flight crews. The dashboard display system's key functionalities include real-time flight monitoring, which displays critical flight parameters such as flight duration, cloud seeding duration, and flight path for operational aircraft. The system also offers insightful data visualizations that cover weekly, monthly, and seasonal trends of hail suppression efforts, providing a wealth of information that supports the users with a comprehensive understanding of the operations. The dashboard system features a user-friendly frontend interface developed with ReactJS, a high-performance backend run by the FastAPI Python framework for efficient data handling and API development, and SQLAlchemy as the object-relational-mapper to store all flight and hail suppression data.  Additionally, and as an innovative approach, this study explores the use of Large Language Models (LLMs) for text-to-SQL (TTS) conversion, allowing users to submit natural language queries about hail operations, which the LLM translates into SQL queries to retrieve relevant data. The dashboard visual system incorporates additional parameters for operational decisions, such as flight altitude, fuel consumption data, and seeding information. This system is expected to significantly enhance situational awareness for flight crews, providing them with a comprehensive view of the operations. Previously, these users relied on disparate sources of information and less integrated tools to manage their operations. This heightened awareness will help coordinate unit and flight crews to make better decisions and improve hail suppression efforts.