How BlueMix can help in a Natural Disaster

A few minutes back the news headline reads “A powerful earthquake has struck south Asia, with tremors felt in northern Pakistan, India and Afghanistan”. Natural Disasters are becoming a commonplace. Technology can help in predicting about such natural disaster and also can help in relief effort, post disaster. Based on my involvement in Uttarakhanda Disaster relief and Nepal Disaster relief, I want to share how technology can help in post disaster relief.

Why Cloud?

A solution on Cloud is inevitable because of the following reasons:

  • Location – the Cloud datacenters are physically distant from the area of the natural disaster and applications can keep running even when power and telecommunications are disrupted.
  • Autoscaling – applications designed for Cloud can automatically scale up easily to accommodate the sudden spike in the application usage on the event of disaster.
  • Support for distributed team development – you won’t be tied to inaccessible physical build and deployment servers if you hit a bug at exactly the wrong time
  • On demand pricing – Using the infrastructure only when it is required – Reduces cost of solution. No need to keep the infrastructure ready, waiting for the disaster to strike.

 

DisasterWhy Bluemix?

BlueMix offers many out of the box services that can help in this effort and one need not have to create applications afresh for these. A catalog of IBM, third party, and open source services allow the developer to stitch an application together quickly.

  • Lots of available libraries for Node.JS for implementing pop-up sites like Wikis
  • Language translation with Watson can be helpful for displaced persons whose first language is not English
  • Twilio can integrate into SMS messaging and VOIP phone networks

How ETL tool like Information Server can help?

We can use the following functionalities of InfoSphere Information Server in Disaster Management

  • Data Standardization: Lot of Data about the location or disaster victims is passed around. This comes from various sources and can be dirty or unusable. Data Standardization service can do data cleansing to remove noise and make it usable.
  • Data Matching: Victim information needs to be dynamically communicated between disaster relief team and the friends and relatives of the victim. These two different sources need to find each other and exchange information. Probabilistic Matching algorithms become inevitable to bring these two together.

These are some of my thoughts. Please share yours so that others can learn and benefit …

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