## 1 Introduction  
The scarcity of water is one of the most important challenges facing the world. Therefore, water consumption and irrigation management have received significant attention. Conventional irrigation consumes large amounts of water through dissipation and drainage. Therefore, it is considered to be one of the highest forms of water consumption in the world. Moreover, conventional irrigation methods sometimes have negative effects on the quality of agricultural crops due to over- or under-irrigation. Therefore, it has become necessary to propose smart irrigation techniques aimed at reducing water consumption without affecting the quality of agricultural crops. Using recent technologies such as wireless sensor networks (WSNs) and the internet-of-things (IoTs) can achieve this aim [1, 2, 3, 4, 5, 6]. WSNs consist of many distributed low-cost sensors which monitor and collect data from the surrounding field and forward it to a gateway for further processing. These sensors are typically distributed across a geographical area, and they can monitor a diverse range of environmental parameters, making them a fundamental element of the IoTsecosystem [2]. They find application in various sectors, including but not limited to; agriculture, environmental monitoring, healthcare, traffic management, and security and safety [2; 3; 4; 5; 6; 7; 8; 9]. In last few years, WSNs have been applied to the agricultural sector to overcome the limitations of conventional irrigation. Using WSNs in the agricultural sector can achieve several benefits, such as reducing water consumption, achieving better crop quality and quantity, conserving energy and reducing costs, and saving farmers time and effort. To obtain these benefits, we design and implement a smart irrigation technique that utilizes WSNs to monitor important environmental parameters, such as humidity, temperature, and soil moisture, which results in superior smart and automatic cultivation. Smart irrigation systems represent a technological leap forward in the domain of agriculture, offering an intelligent and data-driven approach to water management [7; 8; 9]. These systems integrate advanced technologies, such as WSNs and the IoTs, to monitor and analyze key environmental parameters like soil moisture, temperature, and weather conditions. By utilizing real-time data, smart irrigation systems enable precise and automated control over the water supply to crops, ensuring that they receive the optimal amount of water needed for growth. The implementation of such systems not only enhances water efficiency but also contributes to resource conservation, as water is applied judiciously based on actual crop requirements. Moreover, smart irrigation systems often incorporate connectivity features, allowing farmers to remotely monitor and control the irrigation process through mobile applications or centralized platforms. This not only streamlines agricultural operations but also empowers farmers with timely insights for better decision-making. Despite the remarkable progress in WSN research and its applications, several challenges persist [10; 11]. Key issues include energy consumption, scalability, security, network lifetime, and limited communication range. These problems hinder the widespread adoption and reliability of WSNs in various domains. One of the most critical challenges in WSNs is the limited energy availability of sensor nodes, which significantly impacts network performance and longevity [12; 13]. Since most sensor nodes rely on battery power, frequent battery replacements or recharging are impractical, especially in large-scale or remote deployments. Energy harvesting techniques, such as solar power, offer a potential solution [14], but their efficiency depends on environmental conditions, making them unreliable for continuous operation. Existing energy management strategies, such as duty cycling and data aggregation, help optimize power consumption but do not fully address the issue of energy depletion in high-traffic areas.