This study addresses the development of a wireless gas sensor network with low cost, small size, and low consumption nodes for environmental applications and air quality detection. Throughout the article, the evolution of the design and development of the system is presented, describing four designed prototypes. The final proposed prototype node has the capacity to connect up to four metal oxide (MOX) gas sensors, and has high autonomy thanks to the use of solar panels, as well as having an indirect sampling system and a small size. ZigBee protocol is used to transmit data wirelessly to a self-developed data cloud. The discrimination capacity of the device was checked with the volatile organic compounds benzene, toluene, ethylbenzene, and xylene (BTEX). An improvement of the system was achieved to obtain optimal success rates in the classification stage with the final prototype. Data processing was carried out using techniques of pattern recognition and artificial intelligence, such as radial basis networks and principal component analysis (PCA).
Towards plug-and-play functionality in low-cost sensor network