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Bright Ideas – 2023

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Bright Ideas is Kingston University’s annual entrepreneurial competition, open to all students across the university. It is a major university initiative to encourage our students to develop key innovations and enterprise skills. It encourages students to be problem solvers and confident presenters, addressing problems that come from their academic and everyday experiences.

2023 marked the 18th year of the Bright Ideas competition. Workshops, Sprints, Heats and the Final Awards Ceremony took place online. The Pitching Final gave students the opportunity to pitch in person to a panel of judges. A diverse set of entries came from programme areas across the university with over 700 Students participating out of which 597 students were from the Engineering, Computing and the Environment faculty. Many students entered as part of their course, where the experience was integrated to equip participants with enterprise skills
to benefit their future careers.

Engineering Category - First Prize Winner: LevelGuard

From left to right are Engineering Students Myles Taylor, Turrell Harper, Nathan Little, Ben Bright and James Crouch – who are Civil & Infrastructure Engineering students. The team was awarded a £1,000 Engineers in Business Prize.

LevelGuard is a complete, modular pedestrian safety solution, compliant with industry standards and guidance.

Engineering Category - Second Prize Winner: Flexi-kerb

Pictured is Bianca Wheeler,  Team Leader of Flexi-Kerb. Other team members (not pictured) are Karl Geisler, Nick White, Aaron Wray, and Edita Zemgulyte – all are Civil & Infrastructure Engineering students. the team won a £250 Engineers in Business Prize.

Flexi-kerb is an innovative new system to protect newly installed kerbs during civil engineering construction.

 

Computer Science Category - First Prize WatchTower

Computer Science Student, Jihun Park, was awarded a £1,000 Engineers in Business Prize

WatchTower minimises farmland fire damage through early fire detection/alert using AI and Heat detection technology equipped on a drone.