Project Grant NA24OARX021G0015
- This EAGER (Early-concept Grants for Exploratory Research) project, awarded by the National Science Foundation's Engineering program (CFDA 47.041), aims to develop and pilot a novel, satellite-based method for faster and more accurate assessment of flood mitigation infrastructure performance across the United States. The $300,000 grant, awarded on September 1, 2025, with a completion date of August 31, 2027, will support research to generate observed flood data to measure the effectiveness of...
- Iseechange Inc. was awarded a $274,381 Project Grant from the National Science Foundation to develop an integrated methodology for using residents' experiences with flood and other climate change events to validate modeling in real time. Under the NSF Technology, Innovation, and Partnerships program, Iseechange will create a community knowledge platform to process user-generated text and photo data submitted by residents on flood occurrences and severity. This platform will analyze the...
- This National Science Foundation (NSF) Small Business Innovation Research (SBIR) Phase I project grant of $274,391 will fund the development of city-scale flood mapping using real-time sensor data. Awarded on September 15, 2022 with a completion date of August 31, 2023, this funding supports research under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084). Specifically, the awardee Hyfi LLC will advance new knowledge on the use of advanced analytics to estimate floods at...
- This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $200,000 to New York University (NYU) to develop collaborative partnerships and co-identify research questions aimed at using flood sensor data to better understand and predict urban flooding, as well as implement community-level actions toward adaptation and mitigation. The key objectives are to: (1) develop and optimize data processing tools to prepare the flood dataset for actionable...
- This National Science Foundation (NSF) Cooperative Agreement, awarded under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program, provides $1,244,153 to support the development of a novel flood forecasting system by Hyfi LLC, a minority-owned small business located in Ann Arbor, Michigan. The project aims to enhance US flood preparedness by combining real-time sensor data with advanced analytics to deliver localized, 24-hour flood forecasts at the municipal infrastructure...
- The U.S. Geological Survey awarded a $499,999 Cooperative Agreement under the Assistance to State Water Resources Research Institutes program (CFDA 15.805) to Cornell University to develop a distributed sensor network that integrates edge-AI and photogrammetric techniques to automate real-time urban flood monitoring and mapping. Key deliverables include: A minimum viable product (MVP) sensor network to map urban pluvial flood extents and depths in real-time, including storm sewer stage...
- This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant award of $400,000 to Clemson University will develop a next-generation flood computing system called "FLOODENGINE" to improve flood forecasting and analytics. The project will leverage smart cyber-physical systems (SCPS) capabilities to optimize data gathering and processing, develop a physics-based deep learning model, and promote knowledge transfer through innovative networks. The goal is to...
- This National Science Foundation (NSF) Integrative Activities program grant of $189,997 awarded to Iowa State University of Science and Technology will develop a data-driven, physics-informed early warning system to predict flood occurrence and support communities in agriculture-dominated watersheds across the Midwestern U.S. The project will integrate complex watershed characteristics, human land use, and management practices into hydrological modeling to improve flood forecasting accuracy...
- This Cooperative Agreement award, funded by the U.S. Geological Survey under the Assistance to State Water Resources Research Institutes (CFDA 15.805) program, aims to improve flood prediction and risk assessment capabilities across the United States. The $165,000 project, running from January 16, 2025 to January 15, 2026, will be carried out by Purdue University. The research team will develop a new computer model that integrates river data, rainfall patterns, city drainage systems, and land...
- This $199,998 federal Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) aims to advance the understanding of the disproportionate impacts of cascading flood events on vulnerable populations, particularly individuals with disabilities. The primary activities include engaging community partners, conducting stakeholder interviews and community listening tours, assessing the feasibility of existing and emerging flood resilience solutions, and mapping the...
PURPOSE: VISIMO PROPOSES A FEASIBILITY STUDY FOR THE DEVELOPMENT OF FLOODWISE, AN AI DECISION-SUPPORT TOOL THAT WILL ENABLE PROFESSIONALS TO EFFECTIVELY PREPARE, ADAPT, AND RESPOND TO FLOODING EVENTS. FLOODWISE WILL AUTONOMOUSLY SCRAPE AND GEOTAG SOCIAL MEDIA IMAGES OF FLOODING EVENTS TO PRODUCE FLOOD DEPTH ESTIMATION MAPS IN REAL TIME. VISIMO WILL CREATE A CUSTOM ALGORITHM THAT WILL GEOTAG SOCIAL MEDIA IMAGES AND VIDEOS IN THE ABSENCE OF EXIF DATA. UNLIKE CURRENT MODELS, VISIMOS MODEL WILL PINPOINT IMAGE LOCATIONS WITH LATITUDE/LONGITUDE COORDINATES, ACCURATE TO 20 METERS, WITHIN NARROW REGIONS. VISIMO WILL SEEK TO ENHANCE AND REFINE THE CUSTOM FLOOD DEPTH ESTIMATION ALGORITHM UTILIZED IN THE BLUPIX FLOOD RESPONSE APP. THE BLUPIX MODEL IS NOT FULLY AUTOMATED, AND ONLY ESTIMATES WATER DEPTH USING STOP SIGNS; VISIMO WILL EXPAND THIS ALGORITHM TO APPLY TO ADDITIONAL OBJECTS AND PROCESS IMAGES CONTAINING REFLECTIONS ACCURATELY. VISIMOS STUDY WILL DETERMINE (1) THE ABILITY TO AUTONOMOUSLY GEOTAG SOCIAL MEDIA DATA; (2) THE EXPANSION AND REFINEMENT OF THE BLUPIX FLOOD DEPTH ESTIMATION ALGORITHM; AND (3) THE OVERALL FEASIBILITY OF THE PROPOSED FINAL ARCHITECTURE. VISIMO WILL PRODUCE A DEMONSTRATION THAT WILL SHOW, FOR FIVE LOCATIONS, THE PIPELINES ABILITY TO ACCURATELY GEOTAG SOCIAL MEDIA IMAGES AND VIDEOS AS NEW OBSERVATIONS FOR ACTIONABLE FLOOD INTELLIGENCE. END USERS SUCH AS FEDERAL EMERGENCY MANAGEMENT AGENCY (FEMA) FEDERAL COORDINATING OFFICERS, NATIONAL GUARD EMERGENCY MANAGEMENT OFFICERS, EMERGENCY MANAGEMENT PROFESSIONALS IN STATE AND LOCAL DEPARTMENTS OF PUBLIC SAFETY AND EMERGENCY MANAGEMENT, GEOSPATIAL INFORMATION ANALYSIS, AND GEOSPATIAL INTELLIGENCE (GEOINT) ANALYSTS MAY USE VISIMOS TOOL TO (1) RESPOND TO FLOODING IN REAL-TIME USING VISIMOS MOBILE APP; (2) PREPARE OPTIMALLY FOR FUTURE EVENTS USING HISTORIC DATA SAVED WITHIN THE APP TO VISUALIZE HOW FLOODING IMPACTED THEIR REGION DURING SIMILAR EVENTS; AND (3) ADAPT TO FUTURE FLOODING EVENTS USING OUR TOOLS HISTORIC DATA TO INFORM POTENTIAL ADAPTATION STRATEGIES, SUCH AS IMPROVING AGING WATER INFRASTRUCTURE, MODIFYING LAND USE, AND REPAIRING AND RETROFITTING FACILITIES. FLOODWISE WILL INCLUDE A VOICE ACTIVATION FEATURE FOR HANDS-FREE MANIPULATION. THROUGH GEOTAGGING SOCIAL MEDIA IMAGES AND VIDEOS, FLOODWISE WILL CREATE AN ENTIRELY NEW DATA SOURCE FROM PREVIOUSLY UNUSABLE CONTENT. DATASETS PRODUCED BY THE TOOL MAY ALSO SERVE AS POTENTIAL SOURCES OF INPUT DATA FOR PHYSICALLY BASED WATER MODELING TOOLS AND FULLY COUPLED EARTH MODELS TO INCREASE THE ACCURACY OF WATER MODELING. VISIMOS CUSTOM GEOTAGGING MODEL MAY ALSO BE MODIFIED AND TRAINED FOR FURTHER USE CASES, INCLUDING GEOTAGGING SOCIAL MEDIA IMAGES AND VIDEOS FOR DISEASE SPREAD MONITORING, URBAN PLANNING, AND NATURAL DISASTER RESPONSE AND MITIGATION.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 2/14/25 | ||
| Not listed | $0 | 8/29/24 | ||
| Not listed | $0 | 8/29/24 | ||
| Not listed | $174.7k | 7/30/24 | ||
| Not listed | $174.7k | 7/30/24 |