## 2 Related Studies  
Researchers have developed several power reduction techniques in their search for an infinite power source for sensor nodes to achieve a limitless life span. This section presents several WSN power reduction methods that can be used in PA. Early studies on energy-efficient PA can be traced back to [PERSON] et al. [6], who developed a WSN based on an agricultural monitoring system. They discovered that the effective communication distance between nodes is more than 200 m in an open-field environment and the average packet loss rate is 7.6%. These authors adopted a sleep/wake algorithm to reduce the power consumption of the WSN. The received power became attenuated and sinusoidal when the distance between a transmitter and a receiver was increased. The sensor node woke up for 30 s every 4.5 min. The power consumption of the sensor node relative to that in traditional operation (i.e., 80 mA) was 53 mA. A power saving of 33.75% was achieved. [PERSON] et al. [25] proposed methods to optimize data transmission and to extend network life by using a prediction algorithm for the energy harvested from a solar cell via environmental shadow detection. The mechanisms sustained network activities in an uninterrupted and efficient manner in the experimental study. However, a solar cell system is generally irregular and extensively influenced by weather changes. The power consumption of a sensor node in conventional operation is 80 mA, whereas power consumption is minimized based on the duty cycle (DC), which is set to a fixed value. The peak current consumption of the sensor node is 4.5, 18, and 20 mA, which corresponds to 10% DC in empty mode, 30% DC in lacking mode, and 100% DC in sufficient mode, respectively. [PERSON] et al. [20] collected environmental parameter data from distributed WSNs. They adopted a sleep/wake strategy to reduce the power consumption of the sensor node in a WSN. The current consumption of the sensor node is minimized to 142 \(\upmu\)A relative to that in traditional operation, which consumes 24 mA, by switching between sleep and active modes in low DC. [PERSON] et al. [26] observed the impacts of climate change on crop fields by using WSNs. The authors adopted a sleep/wake algorithm to reduce the power consumption of WSNs. The data collection method improved the power consumption of the network. The advantages are low cost and ubiquitous monitoring. Moreover, the system can be widely applied to agriculture in developing countries. The Zigbee wireless protocol was configured to operate for 30 s every 15 min (i.e., DC equal to 3.3%). Therefore, the 129 mA power consumption of the sensor node in traditional operation is reduced to 17.25 mA when the DC strategy is adopted. [PERSON] et al. [27] charged batteries via solar energy generation to solve the problem of covering an agricultural field with mobile sensor nodes. The results exhibited a 4% reduction in the number of nodes and a 10% extension of operation lifetime compared with the conventional method. The selection of the leader node was performed by calculating residual energy. In this case, the power consumption of the node can be extended to 90 working days (i.e., consumes 11.11 mA at a battery capacity of 1000 mAh). [PERSON] et al. [28] designed a fish pond management system for fish conservation by using an autonomous solar-powered system. Zigbee can enter into sleep mode to improve the power consumption of WSNs. The results indicated that the system can successfully control the pond's temperature and dissolved oxygen level. The use of a maximum power point tracking (MPPT) charging controller allows the platform to utilize energy higher than 8 W. However, the components of the system, including a solenoid valve, a stepper motor, and a sensor node hardware, consume a high amount of power, i.e., approximately 4 W. Meanwhile, the sensor node components (i.e., sensor, processor, and RF module) exhibit a low power consumption of approximately 207 mW relative to the total consumption.