SBIR/STTR Research Award

SBIR Phase I: Feasibility of an L5 GPS-Based Tsunami Detection and Alerting System

Award identifier e643ff9fc38fcc4d75301ec3478f322ab5e40ecc9bdb610e24b924a959868c99Awarding agency National Science Foundation

Award amount

$274,694

Program and phase

SBIR · Phase I

Award year

2024

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
HYPERKELP INC
Proposal award date
2024-06-01
Contract end date
2025-01-31
UEI
DZAFQK2E2911
Solicitation number
NSF 23-515
Topic code
ET

Research abstract

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in the development and deployment of an effective, affordable, and globally accessible detection and alert system for tsunamis on coastlines worldwide. Tsunamis are among the most significant ways in which the ocean impacts human civilization. With the increasing population density along coastlines and the global rise in sea levels, the potential for tsunamis to cause unprecedented harm is higher than ever. The proposed product providing enhanced wave height and arrival time maps to its customers could provide significantly more timely alerts to at-risk populations, providing them with essential evacuation information and crucial hours to prepare for approaching waves. This could herald a major shift in tsunami preparedness and resilience. This technology offers wide-ranging benefits for various groups and industries such as small island economies, defense operations, and commercial port operators. To develop these capabilities, this project proposes a buoy-deployable software product that takes advantage of new generations of Global Positioning System (GPS) to detect tsunamis at sea, hours before they make landfall. It will use revolutionary advancements in GPS technology, particularly in vertical accuracy, to detect, prepare for, and mitigate the formidable threat of tsunamis. For the first time, new generations of GPS provide sufficient resolution to detect the subtle vertical displacement of the ocean surface caused by passing tsunami waves with a single receiver even in open ocean. The project will focus on the development of novel methods of signal classification using Dense Neural Network (DNN) and optimize them with rapid Machine Learning (ML) methods. This is expected to help demonstrate that tsunami signatures can be perceived in real-time by low-cost and low-power on-edge processing capabilities. When this new on-edge technology is deployed on widespread ocean buoys, it would form a robust tsunami detection network. These buoys will serve as sentinels, capable of sensing distinct sea level changes that signal an impending tsunami. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

4 SBIR/STTR records share this UEI (2023–2025). Reported award amounts total $3,276,992. Reported amounts are not federal obligations.

Phases: Phase I, Phase II – Direct to Phase II, Phase II

Agencies: Department of Defense, National Science Foundation

Agency intelligence

National Science Foundation

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