# Energy-Efficient Wireless Communication Strategy for Precision Agriculture Irrigation Control
## 1 Introduction
Different energy management schemes for WSN in agricultural and environmental monitoring applications have been proposed by the research community, as summarized by [14; 24]. From a pure communication perspective, techniques, such as efficient routing protocols, efficient medium access control, and data-clustering, have been widely used to reduce power consumption, as demonstrated by [25; 26; 27; 28; 29; 30; 31]. On the other hand, the sleep/wake-up method adopted by the duty cycle scheduling and the adaptive sampling rate techniques consider a control-communication approach. In this regard, the work in [32] proposed a power reduction algorithm based on redundant data for an agriculture irrigation system where data transmission is activated after the difference between the soil moisture readings reaches a specific threshold. In this case, moisture dynamics determine the adaptive sampling rate; however, the defined threshold has a fixed value that does not consider the crop-weather characteristics. In [33], the authors analyzed different duty-cycling mechanisms, including the scheduled and the on-demand approaches. In the first one, the node periodically wakes up and communicates; in the latter, the node is awakened as necessary by an external event. Although the on-demand technique can achieve better results, it relies on an additional communication channel. In [34], the authors proposed an improved duty cycling algorithm to reduce the energy consumption in an agriculture field. The algorithm determines the on-off periods based on energy data aggregation at the base station; however, it does not consider the agriculture process dynamics variables. The work in [35] implemented a content awareness communication system where a sufficiently knowledgeable controller manages a WSN by determining whether each sensor should transmit data or not; however, as stated by the authors, this centralized approach may increase the network load. In [36], an adaptive duty cycle scheme was proposed based on the queue size and priority class of a packet to reduce the delay of high priority packets and support time-bounded delivery of priority packets. This approach concentrates on energy savings based on purely communication parameters. The model proposed by [37] describes soil, crop, and weather dynamics for a grass irrigation control system, and we enhanced and applied it to a pecan crop field to implement an adaptive sampling rate sleep/wake-up strategy based on self-triggered control to implement an energy-efficient algorithm to communicate the sensor nodes over a WSN. The main contributions of this paper are: (1) the identification and validation of the specific process dynamics for the pecan crop irrigation system, (2) the implementation of a model-based self-triggered control algorithm to decrease the number of communication messages while still accomplishing control objectives, and (3) the estimation of the energy consumption improvement in the wireless sensor nodes due to the use of this control approach in comparison with the duty-cycle periodical scheduling technique. The rest of this paper is organized as follows: In Section 2, the elements that comprise the closed-loop irrigation system are described, and the irrigation state-space model is identified and validated with measured data. In Section 3, the implementation of the proposed energy-efficient communication strategy based on self-triggered control is detailed. In Section 4, the experimental control performance and power consumption results are presented and discussed. Section 5 summarizes the conclusions and describes future work.