International Business Machines Corporation
Dynamic Determination of Irrigation-Related Data Using Machine Learning Techniques

Abstract:

Methods, systems, and computer program products for dynamic determination of irrigation-related data using machine learning techniques are provided herein. A computer-implemented method includes obtaining irrigation-related data pertaining to a region of interest; determining temporal values corresponding to irrigation activity at the region of interest by performing spatiotemporal analysis of the irrigation-related data; determining amounts of water utilized in connection with the irrigation activity corresponding to the temporal values by applying machine learning techniques to the irrigation-related data; determining types of irrigation activity attributed to the irrigation activity by applying machine learning techniques to the irrigation-related data and determined amounts of water; determining irrigation-related variables pertaining to the region of interest by executing a physical model using, as inputs, the determined temporal values, amounts of water, and types of irrigation activity, wherein the irrigation-related variables include an extent of irrigation activity; and outputting the determined irrigation-related variables to a user.