Kenyan wins Sh8.1m for her pest-detecting innovation
By Fridah OkachiA Kenyan woman, Esther Kimani, has won the prestigious Africa Prize for Engineering Innovation organized by the Royal Academy of Engineering.
Ms Kimani becomes the third woman in Africa and the second woman in Kenya to win such a prestigious award after Edmund Wessels alongside Anatoli Kirigwajjo from South Africa, who were named joint winners in 2023.
Ms Kimani received Sh 8.1million (£50,000), the largest ever awarded in the history of the Africa Prize, which she said will help her develop her device and expand its reach.
“I aim to scale up my Innovation so that it can benefit one million farmers in Kenya in the next five years,” Kimani said.
Ms Kimani who studied Computer Science at the University of Eldoret (formerly known as Chepkoilel Campus of Moi University) from 2015 to 2019, started her solar-powered innovation back on campus.
Her solar-powered innovation uses artificial intelligence and machine learning and can easily detect and identify agricultural pests and diseases at farms.
“Am very happy to win this prestigious award, I look forward to scaling it (her innovation) to other five countries in Africa to help farmers control pests at the farm level,” said Ms Kimani during the award ceremony in Nairobi.
She further added that while growing up she saw her parents losing up to 40 per cent of their crops each farming season, which affected their living standard.
“We are empowering small-scale farmers, many of whom are women, to increase their income,” Ms Kimani said
Her innovation stands out for its capacity to reduce crop losses for smallholder farmers by up to 30 per cent, while simultaneously increasing yields by 40 per cent.
“This device offers a much-needed solution for the five million smallholder farmers in Kenya, who typically lose about 33% of their crops to pests and diseases,” adds Ms Kimani.
She further said the technology works 24 hours seven days promising up-to-date results.
“The detection works 24/7,” she noted. “The camera can detect any pests and disease with an accuracy of 97 per cent.”
Since most of the smallholder farmers have half or one acre, Ms Kimani adds that its camera can detect pests with a radius of 600 meters. “This means one camera can serve 3 acres of land,” she notes.
The device is also affordable as it can be leased for only Sh 386 (£3) per month. It also offers cost-effective methods as compared to hiring drones or agricultural inspectors.
“Am going to use this money to ensure that the device will stretch to a radius of 1500 meters, this will help double the number of farmers to 10,000. Currently I am working with only 5000 farmers,” she reiterates.
Ms Kimani’s victory is not only a personal achievement but a beacon of hope for the future of African agriculture, promising increased productivity and sustainability for smallholder farmers across the continent.
The AI agricultural tool operates by utilising computer vision algorithms and advanced machine learning to accurately detect and identify crop pests, pathogens, and diseases, as well as the specific nature of the infection or infestation.
Once detected, the device sends real-time alerts within five seconds to the farmer via SMS, providing tailored intervention suggestions. It also notifies government agricultural officers about the presence of diseases or pests, aiding in broader agricultural management efforts.