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Kenyan-Developed APP Utilizes ML to Predicate the Migration and Breeding of Locusts

Kuzi is using satellite data, soil sensor data, ground meteorological observation and machine learning technology trained on predict the locusts’ breeding, appearance and migration routes.

According to the FAO, a locust swarm of a square kilometer can devour the same amount of food in one day as 35,000 people. In effort to curb the desert locust outbreak that affected 23 countries, Kuzi — an early-warning AI tool named after locust-eating bird in Swahili — is using satellite data, soil sensor data, ground meteorological observation and machine learning technology trained on predict the locusts’ breeding, appearance and migration routes. The tool also creates heat map to warn of high-risk areas with locust infestation. Kuzi is available to users in countries including Kenya, Uganda, Ethiopia, and Somalia to help them control the pest outbreak. The system will deliver text messages 2-3 months in advance of anticipated attacks to farmers and agriculturists, which are available in for free in languages such as Kiswahili, Somalia and Amharic. (Source)


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