The SCi-Toolset could be applied to tackling the challenges of increasing crop yields; managing nitrogen consumption to reduce environmental impacts; creating flexible solutions which integrate simply with other platforms / technologies and providing up-to-the-minute intelligence taken from a variety of collected data. This allows customers to translate complex information into meaningful solutions to their problems or challenges.
Increasingly sensors are being used to collect information and predict outcomes to aid the consistent yields of crops, providing data points on soil conditions, wind, fertilizer requirements, water availability and pest infestations. Technologies can be deployed to patrol fields and alert to crop ripeness or potential problems and data analytics can assist in determining the best crops to plant, considering both sustainability and profitability.
Understanding the diverse formats and volumes of complex data is where the SCi-Toolset adds value, providing the intelligence that translates into tangible results.
One of Australia’s main state territories, covers nearly a million square miles, and agriculture is the second largest industry. Wheat alone provides over $1 billion in export income, so the economy is highly dependent on a successful infrastructure.
Unpredictable weather affects crop yields, cattle populations and can cause health issues. The government has decided to set up a state-wide monitoring program using cutting edge technology and data analysis tools.
Using the SCi-Toolset large amounts of data can be gathered, analysed, processed, and interpreted over the long term. Through this effective data interpretation, it can enable agencies to improve crop management and foresight of economic modelling.
Australia is not alone in its investment in agri-tech, studies have shown that big data investment in agriculture has increased 80% since 2012.
The SCi-Toolset has the inherent capability to provide visualisation of patterns that emerge from varying data sources such as geolocation cattle tracking, drone footage, soil sensors and weather formations.
By analysing the data over longer periods, newer and more efficient facilities for growing crop types could be built.
The use of the SCi-Toolset to forecast crop yields could provide benefits to local Governments.
Through long term modelling of weather data, significant events such as droughts can be forecasted early enough so that crop management can be more reactive.