Climatic Parameters and Vegetation Effect on Wireless Routing Pattern in Greenhouse

One of the promising areas where wireless sensor network (WSN) application would be essential is in precision farming, especially those involving high value crops. Understanding the behavior of the signal propagates in such environment would be crucial in optimizing the wireless sensor nodes deployment. This paper discusses the experimental implementation of wireless sensor network in mango greenhouse and the effect of climatic parameters and vegetation on the routing pattern of the nodes. The results show that the number of hops increases as an effect of variation in climatic parameters. Nevertheless, the changes in temperature alone do not seem to affect the changes in the pattern of signals routed in the greenhouse significantly contrary to the changes in humidity level. As humidity level decreases, the number of signal routing increases, thus showing more chaotic routing pattern. The presence of vegetation around the nodes helps to preserve humidity level, thus increasees the creation of low cost path for signal to be undertaken, which in the end added to the number of signal hops.

[1]  L. M. Kamarudin,et al.  Modelling indoor propagation for WSN deployment in smart building , 2014, 2014 2nd International Conference on Electronic Design (ICED).

[2]  David Ndzi,et al.  Signal propagation in aquaculture environment for wireless sensor network applications , 2012 .

[3]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[4]  Hui Liu,et al.  A Wireless Sensor Network Prototype for Environmental Monitoring in Greenhouses , 2007, 2007 International Conference on Wireless Communications, Networking and Mobile Computing.

[5]  G. Swamy,et al.  Efficient Broadcasting with Guaranteed Coverage in Mobile Ad Hoc Networks , 2011 .

[6]  Vlado Handziski,et al.  A common wireless sensor network architecture , 2003 .

[7]  Ismo Hakala,et al.  Effects of temperature and humidity on radio signal strength in outdoor wireless sensor networks , 2015, 2015 Federated Conference on Computer Science and Information Systems (FedCSIS).

[8]  D. Puccinelli,et al.  Wireless sensor networks: applications and challenges of ubiquitous sensing , 2005, IEEE Circuits and Systems Magazine.

[9]  M. S. Razalli,et al.  Signal propagation analysis for low data rate wireless sensor network applications in sport grounds and on roads , 2012 .

[10]  David Ndzi,et al.  Improving AODV Performance using Dynamic Density Driven Route Request Forwarding , 2011, ArXiv.