FarmVibes.AI: Multi-Modal GeoSpatial ML Models for Agriculture and Sustainability

AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synth

The recent, exponential rise in adoption of the most disparate Internet of Things (IoT) devices and technologies has reached also Agriculture and Food (Agri-Food) supply chains, drumming up substantial research and innovation interest towards develop

The ICTs are powerful tools for effective Knowledge sharing (KS) and facilitate data accessibility of rural communities. Even so, the direction of development and application of the ICTs in the context of ASEAN is still unclear. Hence, this study aim

Developments in the area of ‘precision agriculture’ are creating new data points (about flows, soils, pests, climate) that agricultural technology providers ‘grab’, aggregate, compute and/or sell. Food producers now churn out food and, increa

This article draws upon data taken from the following: 18 interviews of Iowa farmers who utilise big data when making farm management decisions; 14 interviews of those engaged within big data industry, those involved in the sale and promotion of larg