Harnessing The Power of Artificial Intelligence for Disaster Response and Crisis Management - Harika, Ala; Balan, Gunapriya; Thethi, H Pal; Rana, Ajay; Rajkumar, K. Varada; Al-Allak, Mustafa Abdulhussein (2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE), 2024)
People on every continent today have to deal with the continual threat of disasters, both natural and man-made. Therefore, novel approaches are required to mitigate their negative impacts and ensure the preservation of life. This article investigates the potential ways in which artificial intelligence (AI) could revolutionize the management of crises and the allocation of resources following disasters. When it comes to catastrophe preparedness, response, and recovery, several different types of AI are being utilized. Natural language processing, predictive modeling, computer vision, and machine learning are a few examples. By contrasting the efficacy of conventional approaches with that of AI-driven systems and programs, this study hopes to arrive at the optimal strategy. The approaches being presented are shown to work using real-world data and case studies. The study begins with a comprehensive review of the various approaches and resources utilized in disaster management. Next, we'll go over our proposed solution, which incorporates AI to facilitate data analysis, decision-making, resource allocation, and emergency communication. We test our technique against established gold standards, such as expert opinion and manual data analysis, to ensure it delivers the expected results. Evaluations of AI-based therapies take a variety of aspects into account. Time to respond, precision, distribution of resources, and adaptability are a few of these aspects. Researching this topic further, we came to the conclusion that AI-driven solutions are useful for crisis management and catastrophe response. Programs built using AI can swiftly process and evaluate massive volumes of data. Individuals are able to make wiser choices in less time because of this. Getting meaningful information from disorganized data, like as social media postings and satellite images, makes it simpler to comprehend what's happening in the world around you. Artificial intelligence systems can also change and adapt to new crisis scenarios because of this quality.