Long-Range and Low-Power Automated Soil Irrigation System Using Internet of Things: An Experimental Study

Introduction

Ground and surface water are heavily used by agriculture in the United States. Food crop production is anticipated to rise sharply as the world's population continues to rise. Resources for water are becoming scarcer. Consequently, it is crucial to use water well, particularly for crops like vegetables. Irrigation water management can have a significant impact on vegetable yield and quality since water availability can be either excessive or deficient. By administering only, the necessary amount of water to the crop directly, gardeners can minimise plant water stress during key growth stages with the help of precision irrigation, a contemporary irrigation management technique(S. et al., 2022). In order to accurately regulate the time, rate, and distribution of water as necessary, integrated sensing, decision-making, and control systems must be developed for crop production systems before precision irrigation can be used. Depending on the soil, plant, or weather conditions, irrigation may be used(Bagha et al., 2022).

For precision irrigation, many sensor systems and technologies, such as evapotranspiration (ET), plant-based, and soil moisture-based systems, have been researched and tried. For ET-based irrigation, a Class A pan evaporimeter or a comprehensive set of weather characteristics from a nearby weather station are needed to calculate the ET rate. Vegetable fields and protected culture systems have seen extensive testing and deployment of soil moisture sensor-based precision irrigation. Two indications for the amount of water present in the soil that can be used to implement soil moisture-based irrigation systems are soil volumetric water content (VWC) and soil matric potential (MP). MP uses a unit of kPa to measure the amount of energy needed for water to travel through soil, which is always a negative quantity. In this investigation, MP sensors were chosen instead of VWC sensors. According to early research, soil MP sensors can better fit IoT systems and have shown sensitivity to changes in soil moisture for irrigation of vegetables. One of the main technologies for precise and automated irrigation systems is the sensor network, whether it is wired or wireless. For the purpose of planning cotton irrigation, Vellidis et al. (2008) created and assessed a real-time smart sensor array that could measure soil moisture and temperature. In related research, a drip irrigation system's real-time feedback control was handled by a microcontroller(Vellidis et al., 2008).

For automated irrigation systems, a variety of embedded control technologies have been used, including Xbee-PRO technology and GSM Bluetooth-based remote-control systems. Applications for wireless personal digital assistants (PDAs and “tablets”) and mobile phones have been created to permit remote sensor data collection and control over actual irrigation systems. Four prototype sites in Brazil, Italy, and Spain were used as part of the SWAMP project, which examined the effectiveness of their IoT-based irrigation system. Sensor data is wirelessly uploaded to a server. The data is then made available for analysis and computation via the internet. To enhance irrigation control, Goap et al. (2018) created an IoT-based smart irrigation management system using a machine learning algorithm(Goap et al., 2018). Crop irrigation management has been examined using a variety of wireless technologies in IoT systems, including Wi-Fi, cellular networks (GPRS and LTE), ZigBee, and LoRaWAN. LoRaWAN technology, which has a maximum range of 10 kilometres and requires little power and money, would make it possible for small farms to finance precision irrigation equipment. Originally released in 2015, this technology was created by the LoRa Alliance, a non-profit organisation that supports the LoRaWAN protocol.