Jelena Rodic@jelenar

Our data-driven AI model is using different data sets to rank top 5 schools to be connected in the area, with details and alternatives on the suggested technology and costs. Multiple factors are used for calculating the rank, such as: location, available network infrastructure, population density, terrain, weather conditions impact and cost of implementation and future operational costs By integrating these diverse data sources, the system can build a rich picture of what precedes and accompanies connectivity problems. ​Using these factors, our model can even produce visual maps highlighting the recommended connectivity solution for each school.

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🔍Create AI-driven, open-source solutions to optimize public sector network management in critical areas like predictive maintenance, total cost optimization (TOC), and energy efficiency—enhancing public sector networks' scalability, efficiency, and sustainability in underserved regions. 📅 Join us February 28–March 2, 2025: Participate online or in person in vibrant Barcelona, on the sidelines of MWC 2025, to collaborate with peers worldwide and shape the future of public sector connectivity. 👨‍🏫 Work alongside experienced industry mentors who will provide guidance and insights to elevate your solutions. 💰 $5,000 prize pool for the winners! 🏆 Compete for a chance to join the lablab NEXT incubator program! 🧑🏻‍💻 Don’t wait! Sign up now to secure your spot before the Kick-Off!