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‎en/sitemap.xml‎

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‎projects/aerodrops/index.html‎

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<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=X-UA-Compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.f29f905470be850fbe5fa8929121ac2e8ac265b98aa89dcf7c19f1e41226fb76.css" integrity="sha256-8p+QVHC+hQ++X6iSkSGsLorCZbmKqJ3PfBnx5BIm+3Y=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.3b4e7d87ccbf185dad88221b3d090e5b5225c1c25fd01c1776cbf4e7a6b614ec.js integrity="sha256-O059h8y/GF2tiCIbPQkOW1IlwcJf0BwXdsv056a2FOw="></script><meta name=generator content="Hugo 0.143.1"><meta name=author content="SensorLab"><meta name=keywords content="industry,droplets,sensorlab,comsensus"><meta name=description content="AeroDrops is the first device capable of selectively detecting airborne droplets in real time. The device detects and count respiratory droplets, enabling smart, data-driven ventilation control that helps reducing infection risk – addressing a key public health challenge highlighted during the COVID-19 pandemic.The technology was developed at the Jožef Stefan Institute. To raise the technology readiness level and bring solution closer to the market, the project received funding through RSF-IND call at JSI. Departments F5 and E6 are collaborating with industrial partners Nanotul d.o.o. and Comsensus d.o.o. to develop a market-ready device and further develop the technology."><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/projects/aerodrops/><link rel=alternate hreflang=en href=https://sensorlab.github.io/projects/aerodrops/><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:url" content="https://sensorlab.github.io/projects/aerodrops/"><meta property="og:site_name" content="SensorLab — Jozef Stefan Institute"><meta property="og:title" content="AeroDrops - Selectively Detecting Airborne Droplets in Real-Time"><meta property="og:description" content="AeroDrops is the first device capable of selectively detecting airborne droplets in real time. The device detects and count respiratory droplets, enabling smart, data-driven ventilation control that helps reducing infection risk – addressing a key public health challenge highlighted during the COVID-19 pandemic.The technology was developed at the Jožef Stefan Institute. To raise the technology readiness level and bring solution closer to the market, the project received funding through RSF-IND call at JSI. Departments F5 and E6 are collaborating with industrial partners Nanotul d.o.o. and Comsensus d.o.o. to develop a market-ready device and further develop the technology."><meta property="og:locale" content="en"><meta property="og:type" content="article"><meta property="article:section" content="projects"><meta property="article:tag" content="Industry"><meta property="article:tag" content="Droplets"><meta property="article:tag" content="Sensorlab"><meta property="article:tag" content="Comsensus"><meta name=twitter:card content="summary"><meta name=twitter:title content="AeroDrops - Selectively Detecting Airborne Droplets in Real-Time"><meta name=twitter:description content="AeroDrops is the first device capable of selectively detecting airborne droplets in real time. The device detects and count respiratory droplets, enabling smart, data-driven ventilation control that helps reducing infection risk – addressing a key public health challenge highlighted during the COVID-19 pandemic.The technology was developed at the Jožef Stefan Institute. To raise the technology readiness level and bring solution closer to the market, the project received funding through RSF-IND call at JSI. Departments F5 and E6 are collaborating with industrial partners Nanotul d.o.o. and Comsensus d.o.o. to develop a market-ready device and further develop the technology."><title>AeroDrops - Selectively Detecting Airborne Droplets in Real-Time &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42>
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</a><button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
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<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class="nav-link active" href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container post my-4" aria-role=main><aside class=my-4></aside><article class=mt-4><header class=mb-4><div><h1>AeroDrops - Selectively Detecting Airborne Droplets in Real-Time</h1><p><span>Duration: Jan 2025 &mdash; Dec 2025</span></p></div></header><section class=my-4><p>AeroDrops is the first device capable of selectively detecting airborne droplets in real time. The device detects and count respiratory droplets, enabling smart, data-driven ventilation control that helps reducing infection risk – addressing a key public health challenge highlighted during the COVID-19 pandemic.
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The technology was developed at the <a href=https://ijs.si/ijsw/V001/JSI>Jožef Stefan Institute</a>. To raise the technology readiness level and bring solution closer to the market, the project received funding through RSF-IND call at JSI. Departments <a href=https://www-f5.ijs.si/en>F5</a> and <a href=https://e6.ijs.si/>E6</a> are collaborating with industrial partners <a href=https://nanotul.com/>Nanotul d.o.o.</a> and <a href=https://www.comsensus.eu/>Comsensus d.o.o.</a> to develop a market-ready device and further develop the technology.</p><p>The AeroDrops project receives funding from the Jožef Stefan Institute&rsquo;s RSF-IND call.</p></section></article></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem>
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</a><span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2025 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script><script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>

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<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta http-equiv=X-UA-Compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,viewport-fit=cover"><link rel=stylesheet href="/style.min.f29f905470be850fbe5fa8929121ac2e8ac265b98aa89dcf7c19f1e41226fb76.css" integrity="sha256-8p+QVHC+hQ++X6iSkSGsLorCZbmKqJ3PfBnx5BIm+3Y=" crossorigin=anonymous><script defer type=text/javascript src=https://sensorlab.github.io/scripts/app.min.3b4e7d87ccbf185dad88221b3d090e5b5225c1c25fd01c1776cbf4e7a6b614ec.js integrity="sha256-O059h8y/GF2tiCIbPQkOW1IlwcJf0BwXdsv056a2FOw="></script><meta name=generator content="Hugo 0.143.1"><meta name=author content="SensorLab"><meta name=keywords content="energy,energy grid,artificial intelligence,dynamic stability assessment,monitoring"><meta name=description content="The AI-ASSIST project focuses on developing a real-time dynamic stability assessment (DSA) tool for electric power systems, using artificial intelligence to enhance stability monitoring in response to rapidly changing environmental and technological demands. The project aims to integrate advanced monitoring infrastructure with AI techniques to predict and address potential instabilities in power systems. Organizations involved in this initiative include the University of Ljubljana's Faculty of Electrical Engineering (UL-FE), the Jožef Stefan Institute (JSI), and ELES, Slovenias national transmission system operator. The Jožef Stefan Institute is responsible for developing and optimizing AI techniques for database management and real-time recognition of power system conditions."><meta name=robots content="noindex,nofollow"><link rel=canonical href=https://sensorlab.github.io/projects/ai-assist/><link rel=alternate hreflang=en href=https://sensorlab.github.io/projects/ai-assist/><link rel=icon type=image/png href=https://sensorlab.github.io/images/favicon.png><meta property="og:url" content="https://sensorlab.github.io/projects/ai-assist/"><meta property="og:site_name" content="SensorLab — Jozef Stefan Institute"><meta property="og:title" content="AI-ASSIST: Artificial intelligence based real-time power system stability assessment"><meta property="og:description" content="The AI-ASSIST project focuses on developing a real-time dynamic stability assessment (DSA) tool for electric power systems, using artificial intelligence to enhance stability monitoring in response to rapidly changing environmental and technological demands. The project aims to integrate advanced monitoring infrastructure with AI techniques to predict and address potential instabilities in power systems. Organizations involved in this initiative include the University of Ljubljana’s Faculty of Electrical Engineering (UL-FE), the Jožef Stefan Institute (JSI), and ELES, Slovenias national transmission system operator. The Jožef Stefan Institute is responsible for developing and optimizing AI techniques for database management and real-time recognition of power system conditions."><meta property="og:locale" content="en"><meta property="og:type" content="article"><meta property="article:section" content="projects"><meta property="article:tag" content="Energy"><meta property="article:tag" content="Energy Grid"><meta property="article:tag" content="Artificial Intelligence"><meta property="article:tag" content="Dynamic Stability Assessment"><meta property="article:tag" content="Monitoring"><meta name=twitter:card content="summary"><meta name=twitter:title content="AI-ASSIST: Artificial intelligence based real-time power system stability assessment"><meta name=twitter:description content="The AI-ASSIST project focuses on developing a real-time dynamic stability assessment (DSA) tool for electric power systems, using artificial intelligence to enhance stability monitoring in response to rapidly changing environmental and technological demands. The project aims to integrate advanced monitoring infrastructure with AI techniques to predict and address potential instabilities in power systems. Organizations involved in this initiative include the University of Ljubljana’s Faculty of Electrical Engineering (UL-FE), the Jožef Stefan Institute (JSI), and ELES, Slovenias national transmission system operator. The Jožef Stefan Institute is responsible for developing and optimizing AI techniques for database management and real-time recognition of power system conditions."><title>AI-ASSIST: Artificial intelligence based real-time power system stability assessment &mdash; SensorLab — Jozef Stefan Institute</title></head><body><header class="navbar navbar-expand-md"><div class=container><a class=navbar-brand href=https://sensorlab.github.io/><img src=https://sensorlab.github.io/images/sensorlab-white.min.svg alt="SensorLab logo" class="d-inline-block align-top me-2" height=42>
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</a><button class=navbar-toggler type=button data-bs-toggle=collapse data-bs-target=#navbarToggler aria-controls=navbarToggler aria-expanded=false aria-label="Toggle navigation">
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<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class="nav-link active" href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container post my-4" aria-role=main><aside class=my-4></aside><article class=mt-4><header class=mb-4><div><img src=https://sensorlab.github.io/projects/ai-assist/aris_logo_hu_6c53da97bd19da0.jpg alt="AI-ASSIST: Artificial intelligence based real-time power system stability assessment logo" class="me-3 mb-2" height=200 width=200 style=max-width:min(200px,100vw)></div><div><h1>AI-ASSIST: Artificial intelligence based real-time power system stability assessment</h1><p><span>Duration: Oct 2023 &mdash; Sep 2026</span></p></div></header><section class=my-4><p>The AI-ASSIST project focuses on developing a real-time dynamic stability assessment (DSA) tool for electric power systems, using artificial intelligence to enhance stability monitoring in response to rapidly changing environmental and technological demands. The project aims to integrate advanced monitoring infrastructure with AI techniques to predict and address potential instabilities in power systems. Organizations involved in this initiative include the University of Ljubljana&rsquo;s Faculty of Electrical Engineering (UL-FE), the Jožef Stefan Institute (JSI), and ELES, Slovenia&rsquo;s national transmission system operator. The Jožef Stefan Institute is responsible for developing and optimizing AI techniques for database management and real-time recognition of power system conditions.</p><p>The AI-ASSIST project receives funding from the Slovenian Research and Innovation Agency (ARIS) under Grant Agreement No. L2-50053.</p></section></article></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem>
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<span class=navbar-toggler-icon></span></button><nav class="collapse navbar-collapse" id=navbarToggler><ul class="navbar-nav ms-0 ms-md-auto ps-4"><li class=nav-item><a class="nav-link active" href=https://sensorlab.github.io/projects><span>Projects</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/results><span>Results</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/publications><span>Publications</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/people><span>People</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/opportunities><span>Join Us</span></a></li><li class=nav-item><a class=nav-link href=https://sensorlab.github.io/about><span>About</span></a></li></ul></nav></div></header><main class="flex-fill container post my-4" aria-role=main><aside class=my-4></aside><article class=mt-4><header class=mb-4><div><img src=https://sensorlab.github.io/projects/ai-assist/aris_logo_hu_8a34a6db7157cf86.webp alt="AI-ASSIST: Artificial intelligence based real-time power system stability assessment logo" class="me-3 mb-2" height=200 width=200 style=max-width:min(200px,100vw)></div><div><h1>AI-ASSIST: Artificial intelligence based real-time power system stability assessment</h1><p><span>Duration: Oct 2023 &mdash; Sep 2026</span></p></div></header><section class=my-4><p>The AI-ASSIST project focuses on developing a real-time dynamic stability assessment (DSA) tool for electric power systems, using artificial intelligence to enhance stability monitoring in response to rapidly changing environmental and technological demands. The project aims to integrate advanced monitoring infrastructure with AI techniques to predict and address potential instabilities in power systems. Organizations involved in this initiative include the University of Ljubljana&rsquo;s Faculty of Electrical Engineering (UL-FE), the Jožef Stefan Institute (JSI), and ELES, Slovenia&rsquo;s national transmission system operator. The Jožef Stefan Institute is responsible for developing and optimizing AI techniques for database management and real-time recognition of power system conditions.</p><p>The AI-ASSIST project receives funding from the Slovenian Research and Innovation Agency (ARIS) under Grant Agreement No. L2-50053.</p></section></article></main><footer class="container d-flex flex-wrap justify-content-between align-items-center py-3 my-4 border-top"><div class="col-md-6 d-flex align-items-center"><a href=https://sensorlab.github.io/ class="mb-3 me-2 mb-md-0 text-body-secondary text-decoration-none lh-1"><img src=https://sensorlab.github.io/images/sensorlab-color.min.svg style=height:2.5rem>
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</a><span class=text-body-secondary>&copy; 2014&nbsp;&dash;&nbsp;2025 SensorLab, Jozef Stefan Institute</span></div><ul class="nav col-md-6 justify-content-center justify-content-xs-right list-unstyled d-flex flex-wrap"><li class=ms-3><a class=text-body-secondary target=_blank href=https://github.com/sensorlab>GitHub</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://twitter.com/CommSysJSI>Twitter</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://www.researchgate.net/institution/Joef_Stefan_Institute/department/Komunikacijski_sistemi>ResearchGate</a></li><li class=ms-3><a class=text-body-secondary target=_blank href=https://e6.ijs.si/>Department's site</a></li></ul></footer><script async src="https://www.googletagmanager.com/gtag/js?id=G-KQGSFFY1XV"></script><script>window.dataLayer=window.dataLayer||[];function gtag(){dataLayer.push(arguments)}gtag("js",new Date),gtag("config","G-KQGSFFY1XV")</script></body></html>

‎projects/bd4opem/BD4OPEM_logo_hu_ed5872b2e4f2e6e8.png‎

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