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20 December 2024 Advancing Coastal Safety: Integrative Strategies for Rip Current Detection and Prevention Using Satellite Technology and AI Innovations
Surisetty V.V. Arun Kumar, Ramesh M., Ch. Venkateswarlu, B. Gireesh, C. V. Naidu, Rashmi Sharma
Author Affiliations +
Abstract

Arun Kumar, S.V.V.; Ramesh, M.; Venkateswarlu, Ch.; Gireesh, B.; Naidu, C.V., and Sharma, R., 2024. Advancing coastal safety: Integrative strategies for rip current detection and prevention using satellite technology and AI innovations. In: Phillips, M.R.; Al-Naemi, S., and Duarte, C.M. (eds.), Coastlines under Global Change: Proceedings from the International Coastal Symposium (ICS) 2024 (Doha, Qatar). Journal of Coastal Research, Special Issue No. 113, pp. 1011–1015. Charlotte (North Carolina), ISSN 0749-0208.

Rip currents, pervasive along coastal areas, present challenges to beach safety, prompting the implementation of innovative monitoring and detection approaches. This comprehensive study adopts a multi-faceted strategy integrating video-based observations, high-resolution satellite imagery analysis, drifter experiments, and advanced AI technologies to improve rip current identification and enhance public safety measures. Utilizing the Quantitative Coastal Imaging Toolbox (QCIT) on low-cost smartphones and the Video Beach Monitoring System (VBMS) at RK Beach and Rushikonda beaches, respectively, we extract valuable information on rip current existence. Multi-temporal very high-resolution satellite imagery analysis over several years delineates potential rip current zones and explores their seasonal variability, aiming to prevent drownings through measures like beachgoer restrictions or lifeguard deployment. The development of NavIC drifters at SAC, utilizing NavIC signals, enriches our dataset with ground truth validation, enhancing monitoring system accuracy. Satellite-derived nearshore bathymetry, coupled with XBeach modeling, aids in understanding rip current dynamics under varying wave conditions. Ongoing efforts involve AI-based rip current detection algorithms, leveraging machine learning for autonomous identification and prediction. Additionally, we have developed a software solution capable of automatically detecting individuals in hazardous rip current zones, bolstering early warning systems and expediting response protocols. By integrating diverse data resources and cutting-edge technologies, our study not only advances rip current science but also provides actionable insights for policymakers, ensuring sustainable tourism development in coastal regions.

Surisetty V.V. Arun Kumar, Ramesh M., Ch. Venkateswarlu, B. Gireesh, C. V. Naidu, and Rashmi Sharma "Advancing Coastal Safety: Integrative Strategies for Rip Current Detection and Prevention Using Satellite Technology and AI Innovations," Journal of Coastal Research 113(sp1), 1011-1015, (20 December 2024). https://doi.org/10.2112/JCR-SI113-198.1
Received: 23 June 2024; Accepted: 30 July 2024; Published: 20 December 2024
KEYWORDS
Early warning system
NavIC
rip currents
tourism
VBMS
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