SCC-IRG: Edge AI, Biofabrication, and Data Science for Disaster Preparedness and Community Wellbeing in Hawaii

About This Grant

Communities in Hawaii and similar remote, rural, and austere regions often face dynamic local conditions that can impact public infrastructure and well-being. Events such as sudden changes in water quality or air particulates after a disaster can present significant challenges. Effectively monitoring and responding to these events requires timely, localized data, which is often difficult to obtain with existing infrastructure. This Smart and Connected Communities (SCC) project seeks to address this critical gap by enabling neighborhoods to become active participants in data collection and analysis for their immediate surroundings. The project will collaborate with participants across several sites in Hawaii to co-design and build novel, low-cost systems for localized data acquisition. This system will feature customizable sensors that are fabricated via advanced manufacturing processes (3D-printing) and connected to a powerful, portable data analysis platform. By making these tools more readily available to local communities, this project will enable rapid, localized responses to unforeseen events thereby improving community preparedness and providing valuable data for disaster planning and response. This work directly supports the NSF’s mission by integrating research and education to advance national health, prosperity, and welfare. The project’s technical goal is to develop and integrate three core innovations: a low-cost, open-source electronics printer; a scalable, AI-enabled edge computing platform; and a robust framework for participant-based co-design. The research will first establish a novel printing system fabricated from 3D-printed and commercial off-the-shelf parts, dramatically reducing the cost and expertise required to produce high-performance sensors for specific chemical and physical analytes (e.g., heavy metals, pH, organic targets). Secondly, a modular, durable, and low-power AI edge device that interfaces with these printed sensors to autonomously collect, process, and analyze data in real-time, even in remote locations with limited connectivity will be developed. The final thrust of the project validates a community participatory co-design process, ensuring the technology is directly responsive to local needs and that the data generated is accessible and actionable. This integrative approach will produce a complete ecosystem spanning sensor fabrication to data interpretation that can be adapted and deployed to address a wide range of localized data collection needs. 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.