FOCUS: A cost-effective approach for large-scale crop monitoring with sensor networks




Yuan, Yuan
Li, Shanshan
Wu, Kui
Jia, Weijia
Peng, Yuxing

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Current investment in crop monitoring consumes a large amount of financial cost, and how to reduce this cost has been a long-standing problem in agriculture. Traditional crop monitoring approaches are not cost-effective, because they rely on either heavy human labor or intensive computation with expensive instruments. In this paper, we explore the possibility of deploying networked sensor nodes for low-cost crop monitoring. As an example, we compute an important agricultural metric called global leaf area index (LAI) to illustrate the benefit of using sensor networks. We propose an approach called FOCUS that incrementally deploys sensor nodes into farmland to improve the accuracy of global LAI measurements. We design and implement a novel algorithm that calculates the total size of crop leaves with light intensity readings captured by the sensors under the crop canopies. FOCUS not only lowers the deployment cost considerably but also reduces the number of sensors for the long-term monitoring. Through a small-scale field test and large-scale simulations, we validate our design and show its effectiveness in crop monitoring.


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Yuan Yuan; Shanshan Li; Kui Wu; Weijia Jia; Yuxing Peng; , "FOCUS: A cost-effective approach for large-scale crop monitoring with sensor networks," Mobile Adhoc and Sensor Systems, 2009. MASS '09. IEEE 6th International Conference on , vol., no., pp.544-553, 12-15 Oct. 2009