# Energy-Efficient Wireless Communication Strategy for Precision Agriculture Irrigation Control
## 1 Introduction  
Smart farming aims to reduce costs and increase productivity while optimizing natural resources through the processing and analyzing of data obtained from sensor devices [1]. Hence, its implementation requires higher demands for data collection and network communication [2]. Perception, interconnection, and decision-making, through the use of modern technology, comprise the three main tasks for precision agriculture [3]. Crop and environmental variables, such as soil moisture, leaf wetness, air temperature, atmospheric pressure, relative humidity, and solar radiation, are commonly monitored in different agriculture applications [4]. Soil moisture may be the most complex variable to measure due to its high spatial and temporal variability and nonlinear behavior. The relevance of measuring the soil moisture has recently increased as closed-loop irrigation, based on this variable, has become one of the most effective strategies to improve water efficiency by applying the right amount of water to crops at the right time [5]. Typically, closed-loop irrigation systems collect data via the implementation of a wireless sensor network (WSN) over large crop area fields with multiple sensing devices placed in different locations to obtain representative soil moisture values. During the last ten years, different works [6; 7; 8; 9; 10; 11; 12] demonstrated the relevance of soil moisture measurements implemented over a WSN to achieve effective and optimum water utilization for irrigation in large crop areas. Implementing WSNs for agricultural applications requires efficient energy management since several battery-powered sensing devices may comprise the network [13]. Energy is mainly dissipated during communication; therefore, power reduction can be achieved by implementing a sleep/wake-up strategy [14], where wireless devices enter standby mode and stop communication until the next transmission time. One of the early used techniques is duty cycle scheduling [15], where nodes are programmed to turn on and turn off on a pre-established basis; however, this approach presents a trade-off between energy efficiency and sensing quality. Recently, adaptive sampling rate techniques based on process dynamics have accomplished significant energy-efficient improvements by activating transmissions only when relevant measurements are required [16]. From a control perspective, digital closed loops have been traditionally implemented using periodical sampling. However, event-driven aperiodic strategies began gaining attention due to the efficiency improvements achieved in the processing time and data communication [17]. Furthermore, event-driven control demonstrated a considerable reduction in communication messages while still achieving the control objectives [18]. Specifically, self-triggered control (STC) implements model-based algorithms to estimate the next sampling event by predicting the instant where the following measurement should take place based on process dynamics [19]. Recently, different self-triggered implementations over WSN have been proposed [18; 20; 21; 22; 23], obtaining relevant control performance and communication efficiency results. In every case, the experiments were either simulated or conducted on laboratory conditions where the controlled processes had well-known state-space models. The work presented in this paper proposes an adaptive sampling rate energy-efficient communication strategy to reduce power consumption from the remote nodes in a wireless sensor network using self-triggered algorithms to implement closed-loop control for precision agriculture irrigation. The objective is to reduce the number of messages in the network by transmitting sensor data only when relevant while accomplishing the irrigation control objectives of using water efficiently and avoiding unhealthy crops due to water stress. The proposed strategy was evaluated and compared with duty cycle periodical-scheduling implementations in four irrigation areas of a pecan crop experimental field.