# Energy-Efficient Wireless Sensor Networks for Precision Agriculture: A Review
## 1 Introduction  
Wireless sensor network (WSN) technologies have rapidly developed over the years. Ecological phenomena in a vast area can be monitored using pervasive devices called motes or sensor nodes. Battery-powered WSNs comprise several sensors, processors, and radio frequency (RF) modules. The sensor nodes or motes can communicate wirelessly through a communication link and forward their data to a base station or coordinator node by communicating with a gateway. The communication among sensor nodes depends on the merging of diverse sensors from simple (i.e., humidity, pressure, and temperature) to complex (i.e., localization, tracking, micro-radars, and images), thereby allowing WSNs to monitor a wide range of surroundings to obtain precise information from the field [1]. Accordingly, the sensing, storage, processing, and communication capabilities of sensor nodes have continuously increased [2]. WSNs have been used in different applications, such as military, agriculture, sports, medicine, and industry. Agriculture can be considered as one of the most favorable facilities for WSNs to improve food crop yields and minimize the burden of farmers [3]. Several projects have been introduced in the precision agriculture (PA) literature. PA aims to prevent the application of the same management routine to a crop regardless of site circumstances and to improve field management from several perspectives. For instance, PA can minimize the wastage of pesticides for the effective control of weeds, pests, and diseases as well as guarantee that crops receive an adequate amount of nutrients, thereby leading to a highly effective, green agriculture. Specifically, PA is a management strategy that employs information technology to improve agricultural quality and production. PA differs for traditional farming in the sense that this process accurately identifies variations and relates the spatial data to management activities. PA involves five stages, namely, (i) data collection, (ii) diagnosis, (iii) data analysis, (iv) precision field operation, and (v) evaluation [4]. WSNs are used as cost-effective processes to increase agricultural yield. Accordingly, WSNs have been used in different agricultural applications, such as for monitoring climate and using soil nutrient data to forecast the health of crops and the quality of agricultural products. Irrigation planning can be predicted using WSNs by observing weather conditions (such as temperature and humidity) and soil moisture. Other sensor nodes can be added to the existing WSN to improve the parameters of the agricultural monitoring system and to make the network scalable. However, some challenges have hindered the agricultural application of WSNs, such as determining optimum deployment schemes, measurement periods, routing protocols, energy efficiency, cost, communication range, scalability, and fault tolerance [5]. For example, the scattered deployment of sensor nodes with a long data-gathering period can help extend the network lifetime. However, some factors may challenge the selection of the distribution region. When the agricultural field faces many obstacles, the communication link may be weakened or lost as a result of signal attenuation. The sensor nodes in WSNs are supplied from the battery, thereby preventing connections to the main supply in the deployment location. Reducing power depletion and prolonging battery life are imperative for WSNs considering their limited battery power. Although the application of WSNs has increased constantly over the years, the manufacturing of batteries has not developed at the same rate [6]. Therefore, WSNs are mainly limited by their batteries [7]. Among the aforementioned challenges, this paper focuses on energy management and highlights energy-efficient and energy harvesting techniques that can be used in agriculture.