releases: https://cohen.house.gov/media-center/press-releases/congressman-cohen-announces-more-415000-federal-funding-bound-city
Data license: MIT · Data source: dwillis/congress-press
This data as json
| url | title | date | year | month | party | chamber | state | member_name | bioguide_id | domain | scraper | source | date_source | text | has_text | collected_at | updated_at |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| https://cohen.house.gov/media-center/press-releases/congressman-cohen-announces-more-415000-federal-funding-bound-city | Congressman Cohen Announces More Than $415,000 in Federal Funding Bound for City of Memphis | 2018-09-21 | 2018 | 2018-09 | Democrat | House | TN | Steve Cohen | C001068 | cohen.house.gov | legacy | Congressman Steve Cohen (TN-09) today announced that the National Institute of Standards and Technology (NIST) has awarded a grant totaling $417,953 to the City of Memphis. The award will support a project titled Map901: Building Rich Interior Hazard Maps for First Responders. This project will better equip first responders with the tools they need to facilitate their work, and to better serve and protect the people of Memphis and Shelby County, said Congressman Cohen. I'm grateful for all of our fire fighters, law enforcement officers, ambulance drivers, EMTs and all emergency service personnel and first responders for the vital services they provide to our community. I'm pleased that these new federal funds from NIST will help first responders in Memphis work with the most state-of-the-art technology and in-depth, real-time information this technology is critical, as it will increase both for our community's and our first responders' safety. The City of Memphis will collaborate with the NIST's Global City Team Challenge program to collect data from city- and university-owned properties. The city's chief information officer and chief data officer will oversee the aggregation of environmental data including temperature, humidity and ambient sounds to infer scene semantics. Both natural and machine learning approaches will be used to survey and re-survey buildings, producing thorough, updated interior hazard maps. NIST has partnered with different municipalities across the United States since 1901 in promoting urban sustainability through the advancement of technology and science. Decades of collaboration with local governments, nonprofit organizations, academic institutions and private corporations have led to innovative solutions to universal problems. ### | 1 | 2026-03-30T12:14:52Z | 2026-03-30T12:14:52Z |