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December 30, 2019 10:24 am

Crop-Disease Detection in Drones Wins Men’s ‘Great Minds Hackathon’

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Hard at work during the fourth annual Jerusalem College of Technology (Machon Lev) ‘Great Minds Hackathon,’ December 2019. Photo: Michael Erenburg. – An innovative crop-disease detection solution designed for drones was announced as the winner of the fourth annual Jerusalem College of Technology (Machon Lev) “Great Minds Hackathon.”

Efraim Hammer and his group partner, Gamliel Roos, both originally from France, won the hackathon by developing a unique system to detect diseased crops through aerial photos taken by a drone. The challenge was presented by FlyTech, founded by Jerusalem College of Technology graduates, which provides innovative aerial services and implements aerial technologies using commercial UAVs and drones.

“If a crop is already dying, it’s very likely that it contaminates the others around it, so the faster you can detect the dying crop, the better,” said Hammer. “It’s estimated that damage from diseased crops and trees amounts to around $60 billion in loses annually, so if optimized, this has the potential for huge savings.”

More than 100 male Orthodox and ultra-Orthodox Jerusalem College of Technology students from Israel and dozens of other countries took part in the hackathon, working around the clock for 48 hours last week on challenges presented by the likes of Amazon Web Services, OrCam, Elbit Systems, Via, Intel and more.

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The hackathon is run by the LevTech Entrepreneurship Center of JCT, which also includes a pre-accelerator program to help students turn their ideas into products and startups. The winners were chosen by a panel of six judges from Israeli companies.

Working on a challenge from OrCam, JCT international student Yaakov Yeger and his team from Teaneck, NJ, developed a solution to enhance an already existing OrCam product for the visually impaired, which uses a camera attached to eyeglasses to identify objects and individuals. The new development enhances that ability so the glasses can identify people from a longer distance without seeing the person’s face clearly.

“Our solution is another step towards leveling the playing field for the blind,” said Yeger. “This is my first hackathon, and it’s been a cool experience. It’s been great to be in this sort of hub with people working all over the place (on different challenges).”

Other solutions included a system to prevent drivers of automobiles from falling asleep, a system for remote physical therapy through a robotic arm, and a system to alert and prevent children drowning in swimming pools.

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