Data Con LA 2022 - Improving disaster response with machine learning
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Antje Barth, Principal Developer Advocate, AI/ML at AWS & Chris Fregly, Principal Engineer, AI & ML at AWS The frequency and severity of natural disasters are increasing. In response, governments, businesses, nonprofits, and international organizations are placing more emphasis on disaster preparedness and response. Many organizations are accelerating their efforts to make their data publicly available for others to use. Repositories such as the Registry of Open Data on AWS and Humanitarian Data Exchange contain troves of data available for use by developers, data scientists, and machine learning practitioners. In this session, see how a community of developers came together though the AWS Disaster Response hackathon to build models to support natural disaster preparedness and response.
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Data Con LA 2022 - Improving disaster response with machine learning
- 1. Improving disaster response with machine learning Antje Barth Principal Developer Advocate, AI/ML AWS Chris Fregly Principal Specialist SA, AI/ML AWS
- 2. Natural disasters increase in frequency and severity Pressure on organizations involved Technology and/or financial barriers
- 3. AWS Disaster Preparedness and Response program Contributing technology solutions Providing subject matter and technology expertise Contributing resources, such as AWS credits and volunteers
- 4. Use case: Edge storage for data transfer/critical information backup
- 5. Supporting Help.ngo with AWS edge compute Hurricane Dorian response in the Bahamas
- 6. AI/ML in the context of disaster response and relief efforts
- 8. The AWS Disaster Response Hackathon awsdisasterresponse.devpost.com Challenge: Improve disaster response with machine learning December 1, 2021 through February 7, 2022 Total of $54,000 USD in prizes
- 9. Hackathon results 1,488 participants 80+ countries 42 project submissions
- 10. Starting place for ML coders studiolab.sagemaker.aws Am azon SageMaker Studio Lab Learn and experiment with ML using free, no-configuration notebooks in the cloud
- 11. Winning projects Popular datasets, ML tools and frameworks
- 12. Prevention and mitigation Preparedness Response Rehabilitation and recovery The disaster lifecycle Disaster/ crisis
- 13. Prevention and mitigation Preparedness Response Rehabilitation and recovery The disaster lifecycle Disaster/ crisis
- 14. Prevention and mitigation Preparedness Response Rehabilitation and recovery The disaster lifecycle Disaster/ crisis
- 15. Wildfire mitigation: Computer vision ID of hazard fuels Quickly identify and respond to tree disease and mortality using computer vision model to ID diseased and dead trees from open -source available Landsat data. devpost.com/software/wildfire -mitigation -computer -vision-id-of- hazard-fuels github.com/MarjorieRWillner/DisasterHack
- 17. Prevention and mitigation Preparedness Response Rehabilitation and recovery The disaster lifecycle Disaster/ crisis
- 18. Thunderstorm prediction using ML Find correlations between the atmospheric conditions at the time of the lightning strike to predict the occurrence of lightning and thunderstorms. devpost.com/software/lighting -prediction -in-india-using-ml github.com/suryaremanan/Thunderstorm -Prediction -Using-ML
- 19. Prevention and mitigation Preparedness Response Rehabilitation and recovery The disaster lifecycle Disaster/ crisis
- 20. Global fire spread prediction system The tech team at Satellite Vu applied their knowledge of wildfires, satellite imagery, and machine learning to demonstrate a fire spread prediction system. devpost.com/software/global -fire-spread-prediction -system github.com/SatelliteVu/SatelliteVu -AWS-Disaster-Response -Hackathon
- 22. Prevention and mitigation Preparedness Response Rehabilitation and recovery The disaster lifecycle Disaster/ crisis
- 23. DisaVu Direct relief resources to where they are needed most using a sophisticated machine learning approach. devpost.com/software/disavu github.com/SrzStephen/DisaVu
- 25. Prevention and mitigation Preparedness Response Rehabilitation and recovery The disaster lifecycle Disaster/ crisis
- 26. Soteria Use machine learning with satellite imagery to map natural disaster impacts for faster emergency response. devpost.com/software/soteria -yolciw github.com/Soteria -ai/Soteria
- 28. Explore more hackathon projects awsdisasterresponse.devpost.com/project -gallery
- 29. Run the sample code studiolab.sagemaker.aws Am azon SageMaker Studio Lab Learn and experiment with ML using free, no-configuration notebooks in the cloud
- 30. Learn how to get started with data science and ML on AWS
- 31. Practical data science specialization coursera.org/specializations/practical -data-science Practical Data Science on the AWS Cloud Specialization 3 courses 10 weeks of content Video lectures, quizzes, hands-on labs
- 32. Book recommendation: O’Reilly, Data Science on AWS datascienceonaws.com Data Science on AWS: Implementing End-to -End, Continuous AI and ML Pipelines 12 chapters 500 pages Hundreds of code samples
- 33. Additional resources AWS Disaster Response Learn more about AWS Disaster Response efforts AWS Disaster Response Hackathon - Project Gallery Browse the hackathon projects and code repos Data Science on AWS Learn how to get started with data science and AI/ML on AWS Amazon SageMaker Studio Lab Learn and experiment with ML using a no -setup, free development environment github.com/data -science-on-aws/data -science-on-aws youtube.datascienceonaws.com
- 34. Thank you! Antje Barth @anbarth antje-barth Chris Fregly @cfregly cfregly