Agricultural production systems strive to minimise risk and maximise opportunities. To support this, many types of decision support systems have been implemented. With the advances in sensing and networking technology it is now possible to drive decision support systems with very accurate, near real time, data. Machine learning and neural networks are able to do advanced processing of the data sets from sensors and give a greater level of sophistication to decision support tools. With the advances in data collection and processing, the decision support space in agriculture is capable of delivering better seasonal forecasting and analysis of management techniques. This session aims to explore the advances in sensor, networking and processing technology and how this is driving better modelling and decision support in agriculture.
Key topics: Sensor data, Seasonal forecasting, Agricultural Decision Support, Agricultural models