Data-Driven Water Security with Bluemix Apache Spark Service: Spark Summit East talk by Vladimir Stemkovski
0 likes460 views
The document outlines the partnership between IBM and Water Mission, a non-profit focused on providing safe water solutions since 2001. They utilize data analysis, including water consumption and socio-economic data, to address challenges like predicting water shortages and improving community usage of safe water. A sample study in Uganda revealed recommendations such as adding an affordable card replacement program and experimenting with the card system to enhance efficiency.
Data-Driven Water Security with Bluemix Apache Spark Service: Spark Summit East talk by Vladimir Stemkovski
- 1. Data-Driven Water Security with Bluemix Apache Spark Service Vladimir Stemkovski IBM
- 2. Water Mission • Non-profit organization dedicated to bringing safe water solutionswhere needed around the world. • Founded in 2001, based in Charleston, SC • Most of the projects in Africa, South America and Asia • 650+ communitydevelopment and disaster projects currently underway • 2000+ safe water and sanitation solutions built
- 3. Water Treatment Stations (Kiosks) • Living Water™ Treatment Systems • Making clean/safe water from otherwise contaminated water sources • Installed and monitored by Water Mission • Maintainedby local communities • Goal: make the maintenance sustainable
- 5. IBM and Water Mission • Started to work together in 2015 • Multiple on-going joined initiatives – Alerting system – Operational Dashboard – Data analysis • Focus on sustainability
- 6. Data Analysis • Multiple data sources – Water consumption data (all transactions) – Historical weather data (including rainy seasons) – Socio-economic data (income, occupations, agricultural seasons, households, etc.) • Comparing several communities • Trying to answer some tough questions – Can we predict water shortages and water outages? – Can we predict drought conditions? – What can be done to increase usage of the safe water in the communities? • Some of these questions can actually be answered!
- 7. Sample Study • 3 communities in Uganda (Kikondo, Busiro, Dei) • Kikondo – 1+ year in operation • Used Bluemix Apache Spark service with Jupyter notebooks to analyze the data and come up with recommendations on increasing efficiency of the kiosk.
- 8. Conclusions • Add affordable program for replacing lost cards • Conduct experiments with inserting more cards into the system • Consider issuing multiple cards to each household
- 9. Thank You. Contact information or call to action goes here.
- 10. Backup