Mission Description
- Real-World Problem: Urban traffic congestion and vehicle emissions plague cities like Dubai, Abu Dhabi, and Doha. With growing populations, rush-hour gridlock wastes time and pollutes the air. Both the UAE and Qatar are investing in smart city transport – for example, Dubai’s planned “Green Spine” highway will use IoT sensors and robo-trams to streamline traffic , and AI-powered traffic management is expected to cut congestion and greenhouse emissions significantly . Qatar’s new Lusail City integrates trains and trams to reduce private car use, lowering CO₂ by an estimated 1 million tons annually .
- Mission Task: Develop an intelligent transportation solution for a busy city district. Students might create a smart traffic light system that adapts to real-time data or a mobile app that recommends optimal routes and public transit options using AI. Another idea is a prototype of a self-driving shuttle or drone that ferries people between metro stations and popular destinations. Teams should use sensors (or data sets) to simulate traffic conditions and show how their solution eases the flow.
- Key Skills: Programming (for AI or algorithm development), data analysis (traffic patterns), IoT integration (traffic cams or sensors), app development, potentially robotics (autonomous vehicles or drones).
- Expected Impact: The solution will aim to cut commute times and emissions by smoothing traffic flow or boosting public transit use. For instance, smarter traffic systems can reduce energy use in transport by up to 25% through optimized routing . By improving mobility, students support the rise of sustainable, smart cities envisioned in UAE Vision 2031 – which calls for clean energy and mobility innovations in urban development – and Qatar’s smart city initiatives. The mission’s outcomes (less idling cars, more people on efficient transit) lead to cleaner air and a higher quality of life in line with each nation’s vision for resilient, low-carbon cities
Student Goal
Develop an intelligent transportation solution for a busy city district. Students
might create a smart traffic light system that adapts to real-time data or a mobile app that recommends
optimal routes and public transit options using AI. Another idea is a prototype of a self-driving shuttle
or drone that ferries people between metro stations and popular destinations. Teams should use
sensors (or data sets) to simulate traffic conditions and show how their solution eases the flow
Mission Information
Status
Open
Deadline
December 31, 2025
Category
Corporate
Grade
—
Rewards
Recognition, Internships, Prizes
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