Emergency Tweet Categorization and Prioritization

The “Emergency Tweet Categorization and Prioritization System” is an all-encompassing solution aimed at reducing the workload of emergency service departments by classifying and prioritizing tweets. The system utilizes Google's BERT model to increase the effectiveness of the rescue process. In natural language processing and text classification, numerous projects have attempted tweet categorization; however, our project specifically addresses prioritizing tweets for emergency departments. The BERT model is optimized to distinguish the authenticity of the tweets and label the tweets which are related to the fire department, police, and medicals. The train dataset has been balanced through the process of oversampling and undersampling to be able to run smoothly and highly accurately. The model has been able to post an 87% accuracy ratio in predicting authenticity. Some of the future directions include time- and distance-based prioritization of tweets, expanding the system to emergency calls, and designing real-time monitoring and alerting mechanisms.