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Faith

AI & Data Science UDOM

MkulimaAI

Problem Statement

Smallholder farmers in Tanzania face challenges such as late detection of crop diseases, limited access to reliable market price information, difficulty estimating expected yields, and poor connections with potential buyers. These challenges can lead to crop losses, poor farming decisions, and reduced income, especially for rural farmers with limited access to smartphones, internet connectivity, and agricultural advisory services.

Proposed Solution

The proposed solution is MkulimaAI, a digital agriculture assistant that helps smallholder farmers detect crop diseases and receive advice in Kiswahili, predict crop yields and market prices, and connect directly with potential buyers. The platform will be accessible through a smartphone application as well as USSD and SMS, allowing farmers with basic phones or limited internet connectivity to access essential agricultural services.

Innovation

What makes MkulimaAI unique is its inclusive, all in one approach to agricultural decision support. Instead of solving only one problem, it combines crop disease detection with Kiswahili advice, yield and market-price prediction, and direct farmer-to-buyer connections in a single platform. Its key innovation is making essential services available through **USSD and SMS as well as smartphones, allowing rural farmers with basic phones or limited internet access to benefit from digital agriculture.

Expected Impact

MkulimaAI will help smallholder farmers reduce crop losses, make better farming decisions, improve productivity, and access better market opportunities. By providing timely crop-health advice, yield and price predictions, and direct connections to buyers, the platform can help farmers increase their income while reducing dependence on intermediaries. Its USSD and SMS access will also promote digital inclusion for rural farmers who have limited internet access or do not own smartphones.

Standing
AI & Data Science 73.7 pts • #3
Team Members
FK
Faith Kapama
Leader