Abstract
The increase in population growth and demand is rapidly depleting natural resources. Irrigation plays a vital role in the productivity and growth of agriculture, consuming no less than 75% of fresh water utilization globally. Irrigation, being the largest consumer of water across the globe, needs refinements in its process, and because it is implemented by individuals (farmers), the use of water for irrigation is not effective. To enhance irrigation management, farmers need to keep track of information such as soil type, climatic conditions, available water resources, soil pH, soil nutrients, and soil moisture to make decisions that resolve or prevent agricultural complexity. Irrigation, a data-driven technology, requires the integration of emerging technologies and modern methodologies to provide solutions to the complex problems faced by agriculture. The paper is an overview of IoT-enabled modern technologies through which irrigation management can be elevated. This paper presents the evolution of irrigation and IoT, factors to be considered for effective irrigation, the need for effective irrigation optimization, and how dynamic irrigation optimization would help reduce water use. The paper also discusses the different IoT architecture and deployment models, sensors, and controllers used in the agriculture field, available cloud platforms for IoT, prominent tools or software used for irrigation scheduling and water need prediction, and machine learning and neural network models for irrigation. Convergence of the tools, technologies and approaches helps in the development of better irrigation management applications. Access to real-time data, such as weather, plant and soil data, must be enhanced for the development of effective irrigation management applications.
Highlights
Water, considered a limited resource, is still an elementary requirement for life onEarth; the upsurge in population growth and climatic changes over several decades has affected water utilization, and water is in high demand [1,2]
Water use efficiency (WUE) and better yield are the key factors for effective irrigation management application (FAO 2001); this is an important and essential issue to be resolved as the demand to feed the exponentially growing population is high [5,6,7]
The data collected from the farm using the Internet of Things (IoT) devices and cloud platform enable the analysis of data through which several complexities can be visualized and resolved, such as estimation of evapotranspiration and irrigation for the upcoming days, prediction of yield, and scheduling of irrigation based on the acquired value
Summary
Water, considered a limited resource, is still an elementary requirement for life on. Water use efficiency (WUE) and better yield are the key factors for effective irrigation management application (FAO 2001); this is an important and essential issue to be resolved as the demand to feed the exponentially growing population is high [5,6,7]. AquaCrop is a designed simulation model used to simulate the essential factors such as water requirements, growth, biomass production, and harvestable yield of herbaceous crop types [4]. A prescribed static irrigation model will result in a limited scope of improvisation, whereas a dynamic irrigation model would result in high precision Available technologies, such as IoT, machine learning, and cloud-based decision support systems, reduce the complexity of implementing dynamic irrigation optimization. This paper does not discuss the economic betterment or government’s geographical policies that may impact on the solution
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