<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Source Themes on EnRedAndo Me - Carlos Prados</title><link>https://carlos.enredando.me/tags/source-themes/</link><description>Recent content in Source Themes on EnRedAndo Me - Carlos Prados</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>mail@carlosprados.com (Carlos Prados)</managingEditor><webMaster>mail@carlosprados.com (Carlos Prados)</webMaster><copyright>© 2026 Carlos Prados</copyright><lastBuildDate>Thu, 04 Nov 2021 00:00:00 +0000</lastBuildDate><atom:link href="https://carlos.enredando.me/tags/source-themes/index.xml" rel="self" type="application/rss+xml"/><item><title>MEWS - an IoT and Cloud-Based avalanche detection and prediction platform</title><link>https://carlos.enredando.me/publications/mews/</link><pubDate>Thu, 04 Nov 2021 00:00:00 +0000</pubDate><author>mail@carlosprados.com (Carlos Prados)</author><guid>https://carlos.enredando.me/publications/mews/</guid><description>This article introduces a Cloud-based platform designed for detecting and predicting snow avalanches. It emphasizes the process of collecting sensor data, storing it in the cloud, and using it as input for Machine Learning algorithms. The paper outlines the data workflow, system functionalities, and the essential data validation and pre-processing steps required before employing Machine Learning. Additionally, it discusses the integration of these Machine Learning features with the OpenGate cloud platform.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://carlos.enredando.me/publications/mews/feature.jpg"/></item></channel></rss>