Abstract: A plant water need computing system and method for forecasting water need to optimize irrigation efficiency while ensuring that a plant grows at optimal water availability. The plant water need computing system and method use a computational input and output balance model (CIOB model) implemented on a server to calculate irrigation need (IR) predictively. The CIOB model is implemented as a service through a representational state transfer application program interface (REST API). Registered clients get access to the API through a client application. Field identifier is passed by the client application to the CIOB model in an API request. The CIOB model sends an API response to the client application. The API response comprises irrigation need (IR). The CIOB model uses a computational module to calculate the IR and uses machine learning to optimize the plant water need.

Abstract: A plant water need computing system and method for forecasting water need to optimize irrigation efficiency while ensuring that a plant grows at optimal water availability. The plant water need computing system and method use a computational input and output balance model (CIOB model) implemented on a server to calculate irrigation need (IR) predictively. The CIOB model is implemented as a service through a representational state transfer application program interface (REST API). Registered clients get access to the API through a client application. Field identifier is passed by the client application to the CIOB model in an API request. The CIOB model sends an API response to the client application. The API response comprises irrigation need (IR). The CIOB model uses a computational module to calculate the IR and uses machine learning to optimize the plant water need.