A Fuzzy-Logic Approach for Optimized and Cost-Effective Early Warning System for Tsunami Detection

Qayyum, Bushra and Ahmed, Atiq and Ullah, Ihsan and Shah, Syed Attique (2022) A Fuzzy-Logic Approach for Optimized and Cost-Effective Early Warning System for Tsunami Detection. Sustainability, 14 (21). p. 14516. ISSN 2071-1050

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With the economic crisis going around the world, a new approach, “build back better”, has been adopted as a recovery package for various systems. The tsunami detection and warning system is one such system, crucial for saving human lives and infrastructure. While designing a tsunami detection system, the social, economic, and geographical circumstances are considered to be vital. This research is focused on designing a low-cost early warning system mainly for underdeveloped countries, which are more prone to tsunami damage due to a lack of any reliable early warning and detection systems. Such countries require proper cost-effective solutions to address these issues. Previous research has shown that the existing systems are either very costly or hard to implement and manage. In this study, we present a wireless sensor networking model, which is an optimized model in terms of cost, delay, and energy consumption. This research contemplates the techniques and advantages of the intelligence of marine animals. We propose a fuzzy logic-based approach for early tsunami detection, using electromagnetic and pressure sensors, based on the behavioral attributes of turtles and real-time values of earthquakes and water levels.

Item Type: Article
Identification Number: https://doi.org/10.3390/su142114516
1 November 2022Accepted
4 November 2022Published
Uncontrolled Keywords: wireless sensor networks; fuzzy logic; marine behavior; tsunami alert system
Subjects: CAH00 - multidisciplinary > CAH00-00 - multidisciplinary > CAH00-00-00 - multidisciplinary
CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-08 - electrical and electronic engineering
CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
CAH11 - computing > CAH11-01 - computing > CAH11-01-05 - artificial intelligence
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User: Syed Shah
Date Deposited: 10 Nov 2022 17:42
Last Modified: 22 Mar 2023 12:00
URI: https://www.open-access.bcu.ac.uk/id/eprint/13725

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