The world is racing towards innovative ways and techniques to feed the massive human population in the years ahead, leaving behind them more than 500 million subsistence farmers who lack basic understanding of best practices in agriculture and as such harvest less than x 5 and even up to x 50 for some crops than their counterparts in the developing world. Any increase by just a marginal percentage would be a tremendous boost in our attempt to feed the future. In an era where these farmers have more processing power through their handsets than the Apollo's guidance computer that landed Amstrong and team on the moon and back, Cognitive Farms aims therefore at overcoming the 2 main common denominator of low crop yields in Africa which are: 1. illiteracy and 2. poverty
- Illiteracy: The inability to read makes it difficult for farmers to consider basic farming know-how like crop rotation, crop/soil suitability, fertilization/pesticides compositions...By running Machine Learning Algorithms fed by large set of clustered data and spatial analysis, We deliver through images insight and best practices to these farmers.
- poverty: Farming as an economic activity is complex and needs minimal initial investment in soil assessment. Soil analysis cost approximately $60 USD, largely unaffordable for a common African farmer. We have successfully implemented a model that does that and maps crop suitability to the farmer's land parcel soil based on the gps position provided through the handset.
The solution which is highly scalable, could be the solution for more than 500 million subsistence farmers worldwide. We strongly believe that an increase of just 15 to 30% in yields would significatively resorb the potential food deficit for the coming centuries.
In addition, the massive jobless youth on the continent could be motivated to turn to agriculture given the low initial investment.