Rescuing Kerala with Python
Biswas Babu (~biswas) |
In the month of August 2018, Kerala, the southernmost state of India, received 250 % of normal rainfall, resulting in all of its 44 dams to be opened. Over 483 people died due to the flooding caused by the opening of dams and a million people were evacuated.
I started a website (keralarescue.in), written in Django. The main purpose of the site was effective collaboration and communication between authorities, volunteers and public. The site was open source from Day 0. About 1500 developers and volunteers onboard our slack group in a couple of days. Within a week, the community united to forge a critical piece of software that saved thousands of lives.
The site initiated as a portal for refugees to request essential resources like food and water and for volunteers to see their needs, all sorted by geographical location. Additionally, we provided direct information for the government and became the official website later on.
The Minimum Viable Product was delivered in fourteen hours. In the initial days, it was only used by the volunteers and Point of Contacts assigned by the government. Later, when the situation became critical, we started getting rescue requests from stranded refugees. The Github repo of the website went viral, and we started to receive feature requests rapidly. We received more than five hundred pull requests in the span of three weeks.
The story I want to present is about the community and technical aspects of keralarescue.in, how people from different backgrounds came together to build a critical piece of software that saved many lives.
Audience This talk is open to all levels of expertise. Beginners would be inspired to explore the field better to equip themselves at times of need. Intermediate listeners will appreciate the python based technology stack used. Well experienced listeners can use this case study as a successful example of how a community can unite to bring order in chaos.
By the end of the talk, listeners will be reminded of the core values that every open source community is built open: To share, build and update - all for a better end result to serve the world.
Outline Introduction - Kerala floods, once in 100 years The crisis - My world through the news reports The realization - I should try as well The small start - IEEE community discussions that lead to the website The unexpected turning point - How I realized more than resources, lives were at stake The expansion - Many more hands joined in, global support The recognition - Kerala government makes this the official website. The positive impact - stats of how many lives were saved as a result of the website The post - math - A case study of technology for good Power of Open - Community becomes the hero The pursuit - Sphere handbook and similar initiatives The takeaway - Mistakes and lessons for the future
My lightning talk at Pycon India 2018: https://www.youtube.com/watch?v=2BiWTLmhDJ4
Carrol Willing's tweet about the talk: https://twitter.com/WillingCarol/status/1049066492308987909
Chief Minister of Kerala tweeting about keralarescue.in https://twitter.com/CMOKerala/status/1032951513809731585
Github repo https://github.com/IEEEKeralaSection/rescuekerala/
My blog post published at freecodecamp’s medium page https://medium.freecodecamp.org/at-the-eye-of-the-flood-5ddec61a87b8/
Slack channel used for collaboration https://keralarescue.slack.com/
IEEE appreciation event: https://www.facebook.com/IEEEKerala/posts/1826721720730464
IEEE article: http://theinstitute.ieee.org/ieee-roundup/blogs/blog/volunteers-come-together-to-help-survivors-of-floods-in-kerala-india?fbclid=IwAR32rQKtVaHndhXHnDy1-vrPLj6QeNaKbaEU9Zc9_gjoyaqHwdDslq6G9-M
Other news links:
I am a final year Computer Science student from India. I tinker around opensource both communities and projects and have created some on my own. Recently my native place Kerala had the worst flood in its history. I helped to create the official flood coordination website for the government using Django. This website was used to track stranded individuals using their GPS locations, aggregate this data, provide API access to 3rd parties who run their own search and rescue.