WAZIHUB launched a 3-month competition hosted by ZINDI to predict Soil Moisture and allow farmers to anticipate water needs and automate their irrigation schedule.
The competition was possible with 3 months of data collected from the agriculture pilot applications at the University Gaston Berger in Senegal with WAZIUP soil moisture sensors (www.waziup.io).
In numbers we had 677 data scientis enrolled and 6,443 total sessions across 96 countries
The winners of this machine learning competition is Olayinka Fadahunsi AKA DrFad from Nigeria.
| 1st Prize | Olayinka Fadahunsi (Nigeria)| 2,000 USD + 1 Gateway + 3 IoT Kits (each IoT kit is worth 500$) | | 2nd Prize | Hamadi Chihaoui (Tunisia) | 1,250 USD + 1 Gateway + 2 IoT Kits | | 3rd Prize | Jasseur Abidi (Tunisia) | 750 USD + 1 Gateway + 1 IoT Kit | | 4th Prize | Daoudi (Tunisia) | 1 Gateway + 1 IoT Kit | | 5th Prize | Sertac_Ozker (South Africa)| 1 Gateway + 1 IoT Kit |
Note that the 3rd place goes to Ageev Alex from Russia. However, he couldn’t receive the prize because, for this competition policy, only Africa resident were eligible to receive the prizes.
Here is the final leaderboard and more insights into the solutions
We congratulate all the data scientists enrolled. Waziup and Wazihub will make sure the resulting model will be tested to have the expected impact which was to help farmers automate their irrigation and use more efficiently their water resources for a better crop yield. This competition was possible with Zindi and Waziup and Microsoft.
The Wazihub project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 780229.