Agriculture plays a critical role in the global economy, and pressure on
agricultural systems will continue to increase as the world’s population grows. Modern
agricultural techniques should take into account both the increased need for efficiency
and the challenges posed by climate change, which together define the competing
needs for sustainable farming and increased food production. Precision agriculture
(PA) refers to the use of both advanced sensor technologies and state-of-the-art data
analysis techniques in order to develop data-driven decision support systems. PA can
help farmers to optimize crop management through accurate yield prediction and the
timely detection of plant diseases and pests. Similar techniques and sensors to those
used in precision agriculture can be used in the management and monitoring of
livestock or fish farms, which this paper will introduce for completeness. A survey of
machine learning methods will be presented in order to provide researchers and endusers
with an up-to-date starting point for their projects and use-cases.
Keywords: Artificial Intelligence, Crop Management, Data Analysis, Livestock
Management, Machine Learning, Precision Agriculture, Smart Farms, Soil
Management, Statistical Prediction.
