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IBM technology giant in collaboration with the Nigerian startup of agri-tech Hello Tractor has presented a block-block and AI-powered digital portfolio and a decision-making tool for the agricultural sector.
The new tool, according to Solomon Assefa, VP of emerging market solutions and director of IBM Research – Africa, will aim to "digitize, optimize and optimize farm business processes to create efficiencies and new services from campaign to table all over the world".
The motivation for developing the new tool was to optimize current time-consuming processes. "In Sub-Saharan Africa, over 60% of crops are handled manually, with less than 20% managed by tractors," said Assefa. This is an unsustainable model as food demand increases due to growing population growth, which is on average 11 million annually. "In addition, up to 50% of farmers suffer post-harvest losses every year due to poor seeding practices," added Assefa.
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IBM Research, the R & D department of IBM, is developing the technology in their lab based in Nairobi, Kenya. According to IBM, its scientific researchers are working to integrate a number of technologies into the mobile app, such as the Watson Decision Platform for Agriculture, Blockchain, IoT and IBM Cloud.
Assefa said: "The magic behind the idea is what we call an agricultural digital wallet, an AI-based and decision-based support platform that allows you to capture, track and share data instantly, while creating a trust end -to-end and transparency for all the parties involved in the entire value chain of agribusiness ".
The app intends to address a broad cross-section of the agricultural sector including farmers, tractor fleet owners, tractor dealers, banks and financial institutions and government bodies.
The new tool will initially only be available in Kenya, but IBM plans to extend its offer to Kenya, Mozambique, Senegal, Tanzania, Pakistan and Bangladesh, however no precise deadline has been found.
IBM also revealed that for the next phase of the project with Hello Tractor, the company is trying to combine machine learning and image recognition to predict crop quality.
The new mobile app will be tested by a pilot during the first half of 2019.
