Abstract: The targeted management of water resources in agricultural systems has been identified as the key approach of enhancing the sustainability, maximizing the water usage, and improving crop yields in the face of escalating stressors associated with the climate. In this paper, the author discusses how geo-spatial technologies (Geographic Information Systems (GIS), remote sensing and satellite data) can be integrated with Internet of Things (IoT) sensing networks and data analytics structures to make irrigation decisions at finer spatial and temporal scales. The combination allows real-time soil drought monitoring, adaptable to weather-driven irrigation controls, and mechanistic control systems that cut down on the use of water but still keep the crops healthy. The paper provides the state of the art of geo-spatial and IoT-based irrigation systems, measures performance in terms of water savings and farm productivity, and defines implementation frameworks, through a long review of recent academic and applied research. Early indications are that the combination of IoT and geospatial capabilities can save 30 percent of irrigation water consumption without loss of yield and can be used to perform predictive modelling and reactive scheduling that is far better than heuristic irrigation strategies. The main issues are still the standardization of data, the reliability of sensors, the connectivity of the network, and the introduction of machine learning models to optimize irrigation. Further requirements of AI-enhanced decision support models warranted by future research ought to involve field validation across a variety of agro-ecological settings.

Keywords: Geo-Spatial Data, Internet of Things (IoT), Precision Irrigation, Smart Agriculture

Pages: 115-126

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