Unleashing Machine Wisdom

Author:

S. P. Siddique Ibrahim1,Rakshitha Ireddi1,Nithin Uppara1,Namratha Lakkakula1,V. Naga Sai Rahul1,Shaik Mohammed Abdul Kareem1

Affiliation:

1. VIT-AP University, India

Abstract

Embarking on an exploration of disaster resilience, this chapter scrutinizes the potential of AI-driven tsunami early warning systems (TEWS). Focused on the catastrophic potential of tsunamis, the narrative unveils a visionary roadmap, spotlighting artificial neural networks (ANN), and convolutional neural networks (CNN). While the actual implementation lies in the future, the chapter charts a course for stakeholders to metamorphose theoretical frameworks into actionable strategies. Beyond technical intricacies, the narrative emphasizes the transformative impact of proactive disaster management. Envisioning a future where machine learning algorithms serve as vigilant guardians prompts a call for a paradigm shift in coastal safety. The chapter culminates by contemplating a future where the synergy between human intuition and AI enhances our capacity to anticipate, respond to, and mitigate the devastating impact of tsunamis. It paints a compelling vision of a safer coexistence with our dynamic planet, outlining challenges, and pointing towards a more resilient future.

Publisher

IGI Global

Reference40 articles.

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