Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/42462
Title: Plume tracking and prediction of atmospheric dispersion of gases using a wireless sensor network
Authors: Tan, Su Lim.
Keywords: DRNTU::Engineering::Computer science and engineering::Computer applications::Physical sciences and engineering
Issue Date: 2009
Abstract: The funding for this project SUG16/06 was used to support the research activities related to wireless sensor network for plume detection. The project can be divided into two main thrusts: (i) the development of low-cost low-power gas sensors and sensor arrays and (ii) the development of wireless sensor node platform. The main challenges that have to overcome for these sensors are to address the power consumption and cost constraint. While conventional techniques employ wafer fabrication technology to allow circuit integration, such technique usually requires high start-up cost especially for low volume production. Moreover, the sensor fabrication has to go through several post-processing stages before any gas sensors are produced, further increasing the cost and complexity. In this project, a modified printed circuit board technique is attempted with polymer carbon composite sensing materials operating at room temperature to reduce the power consumption. The development of wireless sensor node has been aided by the advancement of integrated circuit (IC) technologies. The initial design was based upon discrete devices employing a microcontroller, a wireless transceiver and a separate data acquisition circuit. These have been superseded by highly integrated system-on-chip (SoC) solutions which were employed in the latest design. Lastly, these two modules were integrated to create the wireless gas sensor node. Most of the objectives listed in the project proposal have been achieved.
URI: http://hdl.handle.net/10356/42462
Schools: School of Computer Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Research Reports (Staff & Graduate Students)

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