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    <title>sensors on DASYA</title>
    <link>https://dasya.itu.dk/tags/sensors/</link>
    <description>Recent content in sensors on DASYA</description>
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    <copyright>© DASYA, IT University of Copenhagen</copyright>
    <lastBuildDate>Tue, 25 Aug 2020 00:00:00 +0000</lastBuildDate>
    
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      <title>IoT and ML enhanced scarecrow</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/scarecrow/</link>
      <pubDate>Tue, 25 Aug 2020 00:00:00 +0000</pubDate>
      
      <guid>https://dasya.itu.dk/for-students/proposals/archive/scarecrow/</guid>
      <description>Invasive bird species can be a serious problem in cities, towns and in agriculture. The common pigeon is a very unwelcome guest on many balconies, roofs, terraces. Conventional scarecrows often show no effect, as these birds are known to be quite intelligent, and capable of learning fast. The idea is to built a sensor/camera enhanced scarecrow that - can recognize birds present within its proximity by means of image recognition - perform counting, reporting and statistics and - take event-triggered measures to scare away unwelcome guests, e.</description>
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    <item>
      <title>Machine learning for acoustic/vibrational analysis of wooden building materials</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/learningfromwoodacoustics/</link>
      <pubDate>Tue, 25 Aug 2020 00:00:00 +0000</pubDate>
      
      <guid>https://dasya.itu.dk/for-students/proposals/archive/learningfromwoodacoustics/</guid>
      <description>For this project, you would be working with a partner company who are looking to re-establish wood as a building material for sustainable architecture, and thus are using sensors for quality control - to detect damages and deterioration in buildings. Wood such as timber may be analyzed by non-intrusive acoustic impact testing and subsequent waveform analysis, and the expectation is that machine learning from such measurements would allow us to detect and classify the internal structure and quality of materials.</description>
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      <title>Tiny embedded machine vision for metering (and beyond)</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/tinyembeddedmachinevision/</link>
      <pubDate>Tue, 25 Aug 2020 00:00:00 +0000</pubDate>
      
      <guid>https://dasya.itu.dk/for-students/proposals/archive/tinyembeddedmachinevision/</guid>
      <description>There is currently a lot of progress in really small, yet powerful visual machine learning / computer vision, on hardware like the OpenMV Cam H7, Arduino Portenta Vision Shield, Luxonis LUX-ESP32, Himax WE-I Plus, Arducam Pico4ML, and Raspberry Pi, and on software platforms such as TinyML or OpenMV IDE.
While many popular use cases stem from fields like traffic analysis, wildlife monitoring, we propose to explore the potential of these techniques for a seemingly simple, yet very important field: the retrofitting of leagcy meters and displays, i.</description>
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      <title>Wind turbine non-invasive instrumentation</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/3-wind-turbine-non-invasive-instrumentation/</link>
      <pubDate>Mon, 16 Dec 2019 00:00:00 +0000</pubDate>
      
      <guid>https://dasya.itu.dk/for-students/proposals/archive/3-wind-turbine-non-invasive-instrumentation/</guid>
      <description>The goal of the project is to explore new ways of gathering data about wind turbines as well as local wind/weather conditions. To this end, sound/vibration-based and/or image-based instrumentation as well as innovative experiments such as balloons and light weight weather stations might be considered.</description>
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    <item>
      <title>Sensors at Sea - Maritime IoT</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/maritimeiot/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      
      <guid>https://dasya.itu.dk/for-students/proposals/archive/maritimeiot/</guid>
      <description>Deliberately scoped very wide, this group contains a number of projects in different possible directions, from
 Location services via LPWAN time-of-flight and GPS/GNSS, Vessel tracking and management in fisheries, tourism and logistcs Water quality anc chemistry sensing for Aquaculure, specifically Mariculture, Wave and tidal dynamics, e.g. in energy harvesting
 and variations/combinations of these - targeting locations as diverse as the Øresund, the Orkney Islands and Zanzibar. In all theses places, we work with partner orgnaisations from academic and private sectors.</description>
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