WORLD SIGNAL monitors real-world systems: earthquakes, wildfires, internet connectivity, aviation and more, to detect unusual activity across the planet. Explore anomalies, compare them with historical baselines, and investigate the evidence behind every signal.
Today I m thinking about internet disruptions, aviation, seismic activity, weather, public alerts and news. If you could add one new real-world data source, what would it be?
WORLD SIGNAL correlates changes across internet activity, aviation, infrastructure and external reporting. I m curious where users would draw the line between interesting anomaly and actionable event.
One of the design choices in WORLD SIGNAL is to explicitly say when the data shows something unusual but there isn t enough external evidence yet to explain it. I d love feedback on whether that transparency is useful or frustrating.
I used Vercel to deploy WORLD SIGNAL's Next.js application and server-side API layer.
The biggest capability it gave me was the ability to treat the frontend and backend as one continuously deployable product. I could go from an idea or new data source to a production experiment very quickly, without spending time managing infrastructure.
That shaped WORLD SIGNAL significantly. Instead of building a heavy data platform first, I could start with the user experience: the live globe, signals and anomaly exploration and progressively connect real-world data sources behind it.
As a solo builder, that iteration speed matters a lot: every change can become a live, testable product within minutes rather than another infrastructure task.
Hey Product Hunt π
I built WORLD SIGNAL because I became fascinated by a simple idea:
We have an incredible amount of public data about our planet, but almost no way to see when those systems start behaving differently.
Earthquakes are in one dataset. Wildfires in another. Internet connectivity somewhere else. Aviation somewhere else again.
Individually, each tells a small part of the story.
WORLD SIGNAL tries to connect that picture.
Instead of asking βWhat's happening in the world?β, it asks:
βWhat's unusual right now?β
It continuously compares observed activity with historical baselines and surfaces meaningful deviations across real-world systems.
Every signal exposes the underlying evidence, methodology, timestamp and source. The goal isn't to have AI guess what's happening: it's to make observable changes easier to investigate.
I'm currently experimenting with earthquakes, wildfires, internet connectivity and aviation, with more systems coming next.
This started as an experiment in making invisible global systems visible, and there's still a lot I want to explore.
I'd especially love feedback on one question:
What signal about the world would you want WORLD SIGNAL to monitor next?
Thanks for checking it out π
World Signal
World Signal