AWS Public Sector Blog

Tag: Machine Learning

City of Louisville Builds Open Source Traffic Tools using Data, Collaboration, and the Cloud

Cities spend hundreds of thousands of dollars every year to do point-in-time traffic studies. Those studies assist cities in planning traffic signal timings and detours during street-closures. The City of Louisville, Kentucky, was paying every year for traffic studies and analysis and was getting static reports back. Instead, Louisville decided to use real-time congestion data freely available to governments through the Waze CCP (Connected Citizens Program). Combined with other information like built environment data and collision reports, Louisville could bring this together in the cloud for advanced analytics.

Changing the World, One Artificial Intelligence (AI) Application at a Time

There is no one-size-fits-all profile of the ideal artificial intelligence (AI) and machine learning (ML) customer, user, or developer. AWS is making AI and ML technologies more accessible with managed services that let anyone embed intelligence into their applications. It is why some of the most exciting uses for AI and ML are coming from unexpected places – public sector organizations with a mission to make the world a better place. Learn from some of the many public sector customers re-defining what it means to use AI to solve big challenges.

Using Data in Education: Four Steps to Success

Educators are increasingly adopting data analytics to understand and address gaps in education. This includes educators in higher education seeking to personalize student-learning experiences and improve learning outcomes, as well as policymakers looking to understand and scale effective teaching methods, increase efficiency and teaching capacity, among other concerns. AWS’s “Four Steps to Success” offers a high-level guide for leaders seeking to adopt new tools to make better use of the data they are collecting.

Helping to End Future Famines with Machine Learning

The United Nations, World Bank, and International Committee of the Red Cross (ICRC) with support from Amazon Web Services and other technology companies, recently launched the Famine Action Mechanism (FAM). The FAM is the first global mechanism dedicated to preventing future famines. In the past, responses to these devastating events have often come too late, once many lives have already been lost.

Estimating Hurricane Wind Speeds with Machine Learning

Better estimates of hurricane wind speeds can lead to better decisions around evacuations and general hurricane response planning, saving both lives and property. Hurricane windspeed estimates are currently made using the manual Dvorak technique. The National Hurricane Center releases them every three to six hours. Artificial intelligence (AI) experts with the IMPACT team at NASA’s Marshall Space Flight Center and Development Seed created the Deep Learning-Based Hurricane Intensity Estimator to automate this process.

Highlights from the 2018 IMAGINE: A Better World, A Global Education Conference

Timed with the 2018 back-to-school season, nearly 600 students, educators, university presidents, college administrators, superintendents, and business leaders from 14 different countries met in Seattle, Washington, to discuss how the cloud can address challenges and opportunities facing education. The conference revolved around three core themes: innovation and transformation, the role of machine learning in education, and building the workforce of tomorrow.

Fishackathon: Supporting the Sustainability of our Oceans and Fisheries

According to the World Wildlife Fund, approximately three billion people in the world rely on both wild-caught and farmed seafood as their primary source of protein; yet the United Nations Food and Agricultural Organization estimates that eighty-five percent of marine fish stocks are either fully exploited or overfished. To combat this, the annual Fishackathon, first organized by the U.S. Secretary of State’s Office of Global Partnerships in 2014 and organized this year in partnership with HackerNest, took place in over 40 cities around the globe.