Sana, Newman (2013) Air particle monitoring using image processing. [USQ Project]
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Abstract
Various studies indicated that inhaled microscopic air borne dust particles with diameter less than 10 micrometers (PM10) can cause significant effect on human health such
as heart disease, asthma, stroke, bronchitis and other respiratory diseases. This is due to their ability to penetrate deep into the blood stream and embed themselves in the lung tissue and alveoli.
The aim of this project is to develop a portable low-cost air particle monitoring systems using image processing techniques. Research was conducted on current literatures
based on image processing techniques. Existing methods of monitoring air quality of the surrounding environment has not been fully utilized with image processing techniques. The advances in technology in image processing and its mass uses means it can be afforded at low cost. This system can be commercialised and with the aid of internet protocols the data can be accessible for real-time observation.
A image processing methodology was investigated, developed and implemented. The investigation of this methodology include the investigation on moving images and pro-
cessing of these images frames.
The existing literature was investigated, and image processing techniques for backscattering and reection methods were researched. The researched investigated on frame integration and reduction of noise using normalization and averaging (Yi, Peng & Xiao 2009),(Yang, Xue & Tian 2005a), and conversion of video frames to picture frames. These methods were used in processing of the recorded videos.
When image processing techniques were discovered, the implementation of those techniques was a prototype to detect microscopic particle using methods based on backscat-
tering and reection of light. In the experiments conducted the results evaluated showed a detectable level of different amounts of dust concentration in per cubic meters. Analysis showed that image processing monitoring system designed was a viable option to available air quality monitoring systems in public areas and industries.
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Statistics for this ePrint Item |
| Item Type: | USQ Project |
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| Item Status: | Live Archive |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021) |
| Supervisors: | Leis, John |
| Date Deposited: | 27 Feb 2014 05:19 |
| Last Modified: | 27 Feb 2014 05:19 |
| Uncontrolled Keywords: | air particle; pm10; monitoring; image processing |
| Fields of Research (2008): | 08 Information and Computing Sciences > 0805 Distributed Computing > 080502 Mobile Technologies 11 Medical and Health Sciences > 1116 Medical Physiology > 111699 Medical Physiology not elsewhere classified |
| Fields of Research (2020): | 46 INFORMATION AND COMPUTING SCIENCES > 4606 Distributed computing and systems software > 460608 Mobile computing 32 BIOMEDICAL AND CLINICAL SCIENCES > 3208 Medical physiology > 320899 Medical physiology not elsewhere classified |
| URI: | https://sear.unisq.edu.au/id/eprint/24714 |
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