This Omdena Local Chapter Challenge runs for 5 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.

You will work on solving a local problem, initiated by the Omdena Cracow, Poland Chapter.

The problem

We have seen traction in demand for rural digital advisory services, however current systems for digital advisory are focused on the broad delivery of extension services based on a large number of farmers. AI can revolutionize extension services through the provision of individualized advisory based on several data elements (on-farm data, satellite imagery, remote sensing, and GIS) thereby increasing the value for extension services to the individual farmer. Although use cases are being built in other development agencies and countries, we have not seen greater traction on AI and other technologies integration in IFAD-supported projects. This could be an opportunity to develop a Proof-of-Concept (POC) and develop a potential use case for scale.

The goals

The goals of this project can be broken down into the following:

• Facilitate predictive analytics on production and expected output thereby allowing farmers to know expected output and potential markets based also predictive analysis of market trends based on publicly available market data.
• Make decisions on the potential expected outputs based on analytics of weather and climate and at the same time support decisions on the best input or crop series to produce based on expected quantity and quality vs Production costs.
• Coupled with satellite data and precision technologies predict on best usage of agriculture inputs, soil, and water.
• Change detection application with satellite imagery to understand trends over time.
• Backend image-to-text processing supports farmers understand for example plant disease and its remedy based on information sent to the feature phone via simple SMS or IVR.

Coupled with satellite imagery and geofencing, farms can be tracked on the amount of forest coverage for afforestation: were any trees planted? Were any buildings built? Are fields being irrigated during a period? And the potential carbon that will be offset.

This data can promote investment decisions based on potential tonnage of carbon that will be reduced and credits gained, track and evaluate the carbon or resilience credits. Resilience evolution projection for climate change could be added to the use case to track vulnerability traits.

We encourage applications from teams that can identify, access, and use suitable data to build feasible solutions for any portion of this proposal.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work