Machine Learning-Based Intelligent System for Emergency Response and Disaster Management

Mr P Bujji Babu1|Tirumalasetty Sashi Pavan2|Vallapaneni Ashok3|Muthineni Mahendra4|Thota Venkataramaiah5

doi:10.62643/

Authors

Mr P Bujji Babu1|Tirumalasetty Sashi Pavan2|Vallapaneni Ashok3|Muthineni Mahendra4|Thota Venkataramaiah5 Author

DOI:

https://doi.org/10.62643/

Keywords:

AI Disaster Management, Emergency Response System, Machine Learning, Multi-Output Classification, Disaster Communication, Resource Allocation

Abstract

India is highly vulnerable to natural disasters such as floods, cyclones,
earthquakes, and landslides, leading to significant loss of life and infrastructure. Rapid and
accurate classification of disaster-related messages is essential for effective emergency
response and resource allocation. However, manual systems are slow, inconsistent, and
unable to handle large volumes of data during crises. This study proposes a machine learningbased
disaster message classification system that automatically categorizes emergency texts
into actionable needs such as medical aid, shelter, food, and infrastructure support. NLP
techniques like TF-IDF and lemmatization are used to extract meaningful features from text
data. A multi-output classification model is developed to improve situational awareness by
predicting multiple needs from a single message. This automation enhances response speed,
accuracy, and scalability, supporting efficient disaster management and saving lives during
large-scale emergencies.