Building Climate Resilience in Rural Farming communities with AI-driven Hyperlocal Climate Informatics
User reported climate informatics & pest insights
App, SMS and Voice based interface in local languages
Get insights, report updates, chat and engage in business
A quick look on how we started and what we aim to achieve
Above Anvil Cirrus Plumes are a phenomena that often precede severe weather such as tornadoes, thunderstorms, hail, and high winds. We use Machine Learning to automatically identify AACPs in NASA’s Geostationary Operational Environmental Satellite (GOES)-16 imagery supplemented by radar information. This finds extensive applications in comprehensive automated early warning systems, specifically in areas with very limited number of weather stations & localized sensors.
In remote areas, detecting pests and diseases early is both a challenge and also a necessity. Early detection is challenging with limited resources but is crucial because remote areas have logistical limitations with regard to accessing remedies. Predictive insights are thus very useful. This necessitates both a locally accurate identification system as well as spread prediction to allow for use of sustainable bio-remedies.
In December 2019, Wikilimo co-founder Anurag cycled 600 km through the Spanish countryside to raise awareness about inclusive Climate Action, leading up to the COP25 in Madrid.
At the 2019 Climate Action Summit, Wikilimo Co-Founder Anurag addressed the UN General Assembly, imploring world leaders to provide greater support to Climate Entrepreneurship.
Wikilimo is the winner of the UNDP Unite-Ideas Open Climate Informatics Challenge and the UN Youth Entrepreneurship Competition. Check out the details of the project here.
We love our customers & partners and are actively seeking partnerships with public and private organisations as we prepare for our pilots. Feel free to contact us at email@example.com
Wikilimo is expanding its fully remote core team and hiring for multiple positions. Check out the current openings here.
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