Resilience for Waterfront Infrastructure (“REWIRE”)
Profile last edited on: 12/16/2021

Total Award Amount
Award Phase
Principal Investigator
Matthew Campbell
Activity Indicator

Company Information

Natrx Inc

6220 Angus Drive, Suite 101
Raleigh, NC 27617
   (512) 983-0171
Multiple Locations:   
Congressional District:   04
County:   Wake

Phase I

Phase I year
Phase I Amount
The broader impact/ commercial potential of this SBIR Phase I project is to support sustainable coastal communities and infrastructure facing risks due to erosion, sea level rise, and coastal storms. Approximately 50% of the world’s population lives within 50 miles of the coast and migration toward coastal areas is increasing. The risks to these areas are reflected in the substantial increase in insurance and FEMA claims. This project will research and develop software systems that streamline the analysis, permitting, and implementation of nature-based coastal protection solutions that have been proven to adapt to these risks and provide environmental benefits. This project will develop cross-cutting technologies that will enhance our knowledge of coastal sciences and engineering and leverage nature-based approaches to coastal integrity issues, leading to increasing ecological, cost, and performance advantages compared to traditional manual methods of data collection, analysis and engineering. The empowerment of more resilient coastal communities, enhanced fisheries, and adaptive infrastructure solutions will incentivize private sector investment in these regions. This SBIR Phase I project proposes to develop an integrated software system to prescribe intelligent coastal maintenance solutions through the automated characterization of the relationship of near-shore vegetative indicator species with shoreline protective actions. It is generally understood that shoreline stability is related to nearshore vegetative health, but the difficulty of analyzing and interpreting the complex data sets with certainty levels sufficient to prescribe specific maintenance actions necessitates the investigation and development of a new analytical framework. The principal technical objective is the development of a machine learning and bayesian inference decision support tool incorporating data from existing imagery databases, multispectral UAV imagery, RTK bathymetry, and shoreline maintenance actions for experimental validation. This approach would be applicable to a wide variety of vegetated erosional shoreline systems (i.e. wetlands, coastal dunes, and mangroves). The anticipated result is the technical foundation of a commercial system to more efficiently manage coastal infrastructure risk at lower costs and with enhanced ecological benefits for society.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.

Phase II

Phase II year
Phase II Amount