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DOI

When the fire brigade arrives at a burning building, it is of vital importance that people who are still inside can quickly be found. Smart buildings should be able to expose this location data to the fire brigade working in a smart city. In this paper the feasibility is researched of using ultrasonic sound sensors for human presence detection in smoke-filled spaces. This type of sensor could assist the fire brigade when evacuating a large building by directing them to the places where their help is most needed. The advantage of ultrasonic sound over other sensors or cameras is that its signal is able to pierce through smoke, does not require badges or other wearable devices and introduces little privacy and security risks. In addition, ultrasonic sensors are very inexpensive making it possible to equip every room of a building with an ultrasonic presence detector. In this research both a preliminary ultrasound measuring device and signal processing algorithm have been designed. Testing results show that the walking movement of a person in an indoor area can be detected with the combination of the sensor and the algorithms. In addition, tests of the signal strength in smoke have shown that ultrasound is capable of “looking through” the smoke. The algorithm based on a particle filter allows for more information to be extracted from the relatively simple sensor signal by detecting human walking movement specifically and opens up the way for an ultrasound based indoor positioning system that can be used in emergency situations.
Original languageEnglish
Pages (from-to)135-140
Number of pages6
JournalISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences
Volume4
Issue number4/W7
DOIs
Publication statusPublished - 2018
Event3rd International Conference on Smart Data and Smart Cities - TU Delft, Delft, Netherlands
Duration: 4 Oct 20185 Oct 2018
Conference number: 3
http://sdsc2018.hft-stuttgart.de/

    Research areas

  • indoor positioning, monitoring systems, disaster management, sonar, ultrasound, movement of people, particle filter, doppler signature, smart buildings

ID: 47928829