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Smart heterogeneous precision agriculture using wireless sensor network based on extended Kalman filter

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Abstract

Smart heterogeneous precision agriculture (SHPA) using a wireless sensor network is introduced for limited energy sensor nodes, deployed in an agricultural farm which is divided into a number of heterogeneous agricultural areas. At each time step, the extended Kalman filter is adopted to measure and to predict the agricultural parameters including the soil moisture and temperature so that the noise associated with noisy measurements is filtered. After that, sensor node selection algorithm proactively selects the sensor nodes for each individual area to sense the agricultural parameters. Thus, the network lifetime and sensing accuracy are improved. The sampling interval for each crop is predefined based on the crop types and agricultural requirements so that the crop yields are improved. Also, the design, framework, algorithms, and architecture of SHPA are considered and proposed. Compared with other schemes, simulation results show that the proposed SHPA scheme eliminates the noise associated with the measurements, improves the network lifetime and sensing accuracy, and enhances the crop yields.

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Acknowledgements

We would like to express our thankfulness to Ibhath Project (Qatar Charity at Palestine) which funds this research.

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  1. Department Computer Science, Faculty of Applies Sciences, Al-Aqsa University, P.O. Box: 4051, Gaza, Palestine

    Yousef E. M. Hamouda & Mohammed M. Msallam

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  1. Yousef E. M. Hamouda
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  2. Mohammed M. Msallam
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Correspondence to Yousef E. M. Hamouda.

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Hamouda, Y.E.M., Msallam, M.M. Smart heterogeneous precision agriculture using wireless sensor network based on extended Kalman filter. Neural Comput & Applic 31, 5653–5669 (2019). https://doi.org/10.1007/s00521-018-3386-4

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