Artificial Intelligence (AI) to promote practices about efficient water use in regenerative agriculture, to contribute in the climate change mitigation
Abstract
Based on the estimations for 2050, world population and demand for food will increase, requiring from farmers to produce more food with fewer resources. This project was designed aiming the use of Artificial Intelligence (AI) to improve practices about efficient water use in regenerative agriculture, thus reducing the impact of groundwater depletion in desert areas of agricultural pumping specifically in the area of Ascension, Chihuahua. For this purpose, soils samples will be analyzed defining physical-chemical profile and geospatial distribution of their textures, before installing Sensoterra humidity sensors. Climatological data will be collected to calculate crop evapotranspiration and water stress, then irrigation schedules will be programmed using the Hargreaves-Samani method. The Normalized Vegetation Index will be measured by means of telemetric sensors using a drone type Ebee. These instruments will be connected to a Gateway which will feed a Data Lake through the Microsoft Azure platform. To increase the precision in data collection, to estimate crop evapotranspiration and to program a geoinformatical application which can be used to generate irrigation schedules, will be expected from this project. This is an innovative proposal that will allow Ascensión farmers to receive information in real time about the needs of their crops, improving the decision-making process based on data, avoiding using more supplies than necessary, which will directly impact on the profits, as well as improving regenerative agriculture practices and raising awareness in the local population about how to protect water as the main resource for sustainability.Keywords:artificial Intelligence; evapotranspiration; water management; regenerative agriculture.
Entidad legal responsable del estudio Universidad Autónoma de Ciudad Juárez.
Financiamiento CeTraTecIA/ MicrosoftAIfor Earth / IA CENTER / 800071 CONACYT.
Conflictos de interés Sin conflicto de interés
Publication Citation Carol L. Muñoz Ávilaa, Dr. Alfredo Granados Olivasa*a Departamento de Ingeniería Civil y Ambiental, Maestría en Estudios y Gestión Ambiental, Instituto de Ingeniería y Tecnología, UACJ. *Autor de correspondencia. Correo:[email protected]
URL https://erevistas.uacj.mx/ojs/index.php/memoriascyt/article/view/4742
University Universidad Autónoma de Ciudad Juárez
Publication date Nov. 18, 2021
