The impact of a weather event generally depends on exactly where your property lies within the event’s boundaries. Then there are the other variables like terrain, soil type and plantings, which all play their part in any outcome. The impact on your property may be completely different to that on your neighbours’ properties.
Growers constantly grapple with complex decisions that impact their crops, resources and day-to-day operations in the field. Unfortunately, these decisions are often based on unreliable, inaccurate, or limited-scope weather information. The existing weather data is not localised enough, and conventional forecasts lack the necessary level of detail for effective planning.
A new research project, Using AI and machine learning to improve weather forecasting (AS23005), looks at addressing these challenges by integrating AI and machine learning into hyper-localised weather forecasting.
The project aims to empower farmers with more accurate, contextually-tailored insights, enabling them to make more informed decisions about frost protection, spraying practices, irrigation, growth management and pest control.
Improving accuracy = increased productivity
The project’s overall purpose is to increase the productivity and yield of Australian horticulture farming operations by improving the quality and accuracy of weather forecasting information, considering the grower’s unique terrain and operational requirements.
This project will develop and trial an on-farm machine learning and artificial intelligence (AI) data-driven, hyper-localised weather forecasting platform for Australian horticultural growers. It will provide tangible results that will directly inform the commercialisation of the Jane’s Weather platform, enhancing the industry’s weather forecasting capabilities.
It will develop a transformative approach that will bring greater precision to farming operations by bridging the gap between data scarcity and the intricacies of agricultural demands.
The project Using AI and machine learning to improve weather forecasting (AS23005) is funded by Hort Innovation using the Advanced Production Systems Fund. There’s more information on other Advanced Production Systems Fund projects here.
