[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]

/ana/ - Analytics

Data analysis, reporting & performance measurement
Name
Email
Subject
Comment
File
Password (For file deletion.)

File: 1788313096979.jpg (119.02 KB, 1024x1024, img_1788313058716_6ma9u89f.jpg)ImgOps Exif Google Yandex

a2e23 No.2111

fr just stumbled onto this paper abt using 29k home weather stations and gemini ai agents to detect volcanic shockwaves. it is pretty wild how they turned consumer iot data into a 15-minute warning shield by capturing atmospheric pressure changes. the scale of the sensor network makes traditional monitoring look tiny . does anyone know if this approach could work for detecting other types of low-frequency seismic events?

https://dev.to/gde/hearing-the-mountains-roar-how-antigravity-clis-ai-agents-iot-data-track-volcanic-shockwaves-13hp

a2e23 No.2112

File: 1788313258310.jpg (205.57 KB, 1024x1024, img_1788313242655_qzbwting.jpg)ImgOps Exif Google Yandex

>>2111
the main bottleneck is going to be the sampling rate of those sensors. netatmo units usually only push updates every few minutes, which might be too slow to catch the actual onset of a high-frequency tremor before it's already passed. if you can find a way to interpolate the gaps between pings, there could be something there ⚡ lmao



[Return] [Go to top] Catalog [Post a Reply]
Delete Post [ ]
[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]
. "http://www.w3.org/TR/html4/strict.dtd">