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Project Story

Our team built NetworkNudge during MadHacks 2025, inspired after talking with Matt and several representatives from TDS Telecom, who described how difficult it is to gain real-time visibility into routing decisions and signal health. Their insights motivated us to design a platform that makes complex network paths understandable for both engineers and customers.

We modeled realistic fiber behavior by simulating how signal strength fades gradually along each connection and how different link characteristics influence the final quality. Specifically, the signal decay along each link is handled using:

$$ \text{new_quality} = \text{current_quality} \times \left(10^{-\frac{\text{degrade_rate}}{10}}\right)^{\text{distance}} $$

We also created an edge scoring system to weigh different routing factors:

$$ \text{Edge Score} = w_{\text{latency}} \cdot \text{latency}{ms} + w{\text{traffic}} \cdot \text{traffic_load} + w_{\text{risk}} \cdot \text{risk} $$

This allows users to compare routes that have different trade-offs in latency, congestion, and reliability. Developing the backend taught us a lot about telecom constraints, routing logic, and the challenges of visualizing dynamic systems. The main obstacle we’re still working through is the frontend display, which currently has rendering bugs that prevent full real-time interaction. Even so, NetworkNudge already demonstrates a strong foundation for clearer network insight and more engaging educational storytelling.

Built With

• flask
• geopandas
• leaflet.js
• next.js
• pandas
• python