Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring.

Sensors (Basel)

National Engineering and Technology Center for Agriculture, Jiangsu Key Laboratory for Information Agriculture, Collaborative Innovation Center for Modern Crop Production, Jiangsu Collaborative Innovation Center for the Technology and Application of Internet of Things, Nanjing Agriculture University, Nanjing 210095, China.

Published: December 2016

Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and -connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA) is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1) nodes must be located in the corresponding plots; (2) WSN must have -connectivity; (3) WSN must have no communication silos; (4) the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect. The deployment experiments were performed on natural farmland and on irregular farmland divided based on spatial differences of soil nutrients. Results showed that both WSNs gave full coverage, there were no communication silos, and the minimum connectivity of nodes was equal to . The deployment was tested for different values of and transmission distance (d) to the node. The results showed that, when was set to 200 m, as increased from 2 to 4 the minimum connectivity of nodes increases and is equal to . When was set to 2, the average connectivity of all nodes increased in a linear manner with the increase of from 140 m to 250 m, and the minimum connectivity does not change.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5191076PMC
http://dx.doi.org/10.3390/s16122096DOI Listing

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