AntiFogo

Earth intelligence system for wildfire prevention, early detection, spread + suppression modelling, and continuous calibration from real-world evidence.

[AntiFogo @AntiFogo_]

CA: 0x87Ee852A12Dc1e108b5EC23337eA4f80fd8B8ba3

[Marco Barbosa @mbarrbosa]

In the last 24 hours, three fires in Portugal were detected well before any agency found out or anyone called in; the average lead time rose from 124 minutes to 127.

This is the result of 7 ML customized models recalibrating and retraining on a corpus of thousands of historic and ongoing wildfires, a few times per hour 🫡

[AntiFogo @AntiFogo_]

Support our wildfire intelligence mission 🔥 🛰️ 🚒

https://t.co/ou0UT4XhXd

[Grok @grok]

Yes, that tracks. The architecture and closed loop are already further ahead than most early wildfire systems. The public face and the compute needed to run the full multi-source cascade at higher cadence are the two clearest gaps between current reality and the ambition. Closing those is the highest-leverage next work.

[Marco Barbosa @mbarrbosa]

Asked @grok to be honest after sharing most of the code and data pipeline of https://t.co/6GmR1s8mPt 🤔

[Marco Barbosa @mbarrbosa]

https://t.co/Hn6DImbSlZ is a free, open wildfire intelligence platform.

But now, we’re preparing the next layer: an advanced intelligence and risk-management workspace for premium users and campaign supporters. 🔥🛰️

[Marco Barbosa @mbarrbosa]

🇵🇹 → 🇪🇸 → 🇫🇷

Today marks the first expansion of @AntiFogo_ beyond Portugal.

Our wildfire intelligence system is now continuously computing across Portugal, Spain and southern France — including the early ignition detection pipeline. 🔥🛰️

[Marco Barbosa @mbarrbosa]

1/ In the past 7 days over Portugal, 30 @AntiFogo_ early ignition alerts were later confirmed as wildfires. 16 were before authorities even knew about them (median ~88 minutes early).

But wins are easy to cherry-pick, so I then audited the system against all 1,122 registered wildland fires of the past 14 days. 🧵

[AntiFogo @AntiFogo_]

👀

[AntiFogo @AntiFogo_]

Wait for it…

[Marco Barbosa @mbarrbosa]

What I’m about to share later today will change everything about wildfires, through @AntiFogo_

Specifically on early ignitions detection intelligence (which directly affects prevention, propagation and suppression).

[Marco Barbosa @mbarrbosa]

@Replit Already improving @AntiFogo_ 👀

[Marco Barbosa @mbarrbosa]

https://t.co/qTrfmvvJTn is now available to the public (a simulation demonstration simplified feature of our command center for professionals).

[Zeno @zenoVision_]

https://t.co/Fw4jNYQksa monitors air quality across 400+ Delhi wards with 10+ data feeds.

State: PM2.5/PM10/NO₂/O₃ per ward.

Transition: LightGBM regressors, 72h ahead, one per hour.

Physics prior: CAMS atmospheric model (our "Newton's laws" layer).

And we have an intervention simulator. Ask: what does Odd-Even actually do to AQI in 48h?

[Zeno @zenoVision_]

From that stack we’ve started building products like:

🔥 AntiFogo — wildfire intelligence

🌫️ AirWatch — atmospheric intelligence

🌍 EarthWatch — seismic intelligence

🌊 SeaWatch — marine intelligence

🌾 AgroWatch — agricultural intelligence

🏙️ UrbanWatch — urban intelligence

Each solves a different problem. Each makes the others smarter.

[AntiFogo @AntiFogo_]

https://t.co/szPrBWE3yB 👀

[Marco Barbosa @mbarrbosa]

Introducing ■ https://t.co/ZhALSVHFzc

Delhi has 40 official air quality monitors for 33 million people.

Most air quality apps give you one number. One city-wide average. Whether you're in Rohini or Vasant Kunj, the number is the same.

We built something different.🧵

[AntiFogo @AntiFogo_]

@XenBH @base @TalentProtocol 🙋‍♂️

[AntiFogo @AntiFogo_]

@baseapp Tokenized communities? 🥹

[AntiFogo @AntiFogo_]

@StreetFDN 🙋‍♂️

[AntiFogo @AntiFogo_]

@0xNairolf on it 🫡