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BALASUBRAMANIAM VEDAGIRI
VICE PRESIDENT
MPHASIS
The Problem Statement
• Natural disasters are caused by
– Floods resulting in traffic disruption, loss of crops,
people, animals etc
– Cyclone devastation in coastal areas
– Earthquake, Landslides, tsunami & Avalanches
• Delayed warning of natural disasters causing
extensive loss/damage
• Absence of relief infrastructure
The Solution – Flood as pilot
• Objective is to identify hot spots based on past
incidents, predict future disasters, aid relief measures,
provide reports for real time analytics in a cost
effective manner with an intent to enable trauma care
with the help of businesses that focuses on trauma
relief
– Early Warning - Effective geo-spatial communication
system & use of analytics and predictive algorithms
– Infra setup - Provide proper means of uninterrupted
infrastructure with redundancy/continuity & Faster and
alternate data connectivity via cloud for cost effectiveness
– Actual relief - Convergence of agencies driven by dedicated
toll-free services for trauma care
The Constraints
• Availability of weather and met data on real-
time basis
• Investments related to setting up redundant
infrastructure
• Power during and post disaster
• Interest/common goal by other agencies
Implementation Steps
• Set-up sensors and M2M platform for flood prone areas
• Tie up with Met/Weather office for satellite data
• Usage of big data to arrive at predictive analytics
algorithm
• Identify Hot-spots, send early warning and invoke
disaster mitigation plans using Push Notification from
cell tower
• Integrated portal for intra-agency coordination for relief
measures
• Set-up toll free services and PRI
• Monitor, track and coordinate relief
• Communication of outcome to all stakeholders
Technologies Used
• Sensors
• M2M, Push Notification from Cell tower
• Toll free services and PRI
• Solr open source enterprise search platform
• Advanced Big data analysis with Cloudera
Hadoop and R
Outcomes
• Accelerated pace of warning
• Reduced damage/loss
• Proactive and timely evacuation
• Effective trauma care
• Enhanced prediction at low cost and <80% loss
• Delivers a flexible solution topology using ‘power of many’
• Improvement of forecasting, warning, communication and
effective pro-active disaster management
• 75% improvement in disaster management than last
year
Thank you

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201 Balasubramaniam Vedagiri (Bangalore)

  • 1.
  • 3. The Problem Statement • Natural disasters are caused by – Floods resulting in traffic disruption, loss of crops, people, animals etc – Cyclone devastation in coastal areas – Earthquake, Landslides, tsunami & Avalanches • Delayed warning of natural disasters causing extensive loss/damage • Absence of relief infrastructure
  • 4. The Solution – Flood as pilot • Objective is to identify hot spots based on past incidents, predict future disasters, aid relief measures, provide reports for real time analytics in a cost effective manner with an intent to enable trauma care with the help of businesses that focuses on trauma relief – Early Warning - Effective geo-spatial communication system & use of analytics and predictive algorithms – Infra setup - Provide proper means of uninterrupted infrastructure with redundancy/continuity & Faster and alternate data connectivity via cloud for cost effectiveness – Actual relief - Convergence of agencies driven by dedicated toll-free services for trauma care
  • 5. The Constraints • Availability of weather and met data on real- time basis • Investments related to setting up redundant infrastructure • Power during and post disaster • Interest/common goal by other agencies
  • 6. Implementation Steps • Set-up sensors and M2M platform for flood prone areas • Tie up with Met/Weather office for satellite data • Usage of big data to arrive at predictive analytics algorithm • Identify Hot-spots, send early warning and invoke disaster mitigation plans using Push Notification from cell tower • Integrated portal for intra-agency coordination for relief measures • Set-up toll free services and PRI • Monitor, track and coordinate relief • Communication of outcome to all stakeholders
  • 7. Technologies Used • Sensors • M2M, Push Notification from Cell tower • Toll free services and PRI • Solr open source enterprise search platform • Advanced Big data analysis with Cloudera Hadoop and R
  • 8. Outcomes • Accelerated pace of warning • Reduced damage/loss • Proactive and timely evacuation • Effective trauma care • Enhanced prediction at low cost and <80% loss • Delivers a flexible solution topology using ‘power of many’ • Improvement of forecasting, warning, communication and effective pro-active disaster management • 75% improvement in disaster management than last year