Lace AI-Powered Optimization for schools
Many schools in remote and underserved regions experience high latency due to distant servers and limited bandwidth capacity, which disrupts digital learning. Our solution applies clustering algorithms (K-Means, DBSCAN) to 2.3 million school geolocations, pinpointing where data centers can most effectively serve 90% of educational content while minimizing latency. Leveraging open-source AI tools (Scikit-learn, Streamlit) and real-time connectivity data from Giga, our approach provides actionable insights for governments, NGOs, and internet service providers. In a user-friendly dashboard, stakeholders can visualize schools’ connectivity issues, compare bandwidth savings across regions, and analyze predicted performance boosts from new data centers. We plan to expand our model globally, ensuring accessible, high-quality internet connections for all schools—and ultimately bridging the educational digital divide.
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"While the solution effectively addresses latency and bandwidth challenges in remote schools, it could benefit from a more detailed plan on how to implement the suggested data center placements and ensure sustainable, long-term support for the regions most in need."
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Jahnavi Anilkumar Kachhia
Software Engineer
"Demo works, presentation is ok. Needs more backend effort."
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Ivan Dotu
"Audio for the video of the presentation didn't work on my end. Solution is tied to the hackathon thematic. Works on the strategic placement of data centers to better serve school content. Would like to see how this works out in other countries that don't have local content but leverage international traffic, for example by adding in layers of IXP points or CDNs. "
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Maria Antonia Bravo
"The presentation needed some more work. But good job, the demo seems very well developed an dthe area based network analysis seems solid"
Shebagi Mitra
Technical Mentor
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