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In Indiana, where agriculture contributes an estimated $35 billion annually to the state's economy, experts believe AI holds the potential to transform the industry's production methods and ...
The integration of AI and IoT in Florida's agriculture is not merely an advancement in productivity. It represents a strong commitment to safeguarding our precious water resources.
An agricultural robot is a robot deployed for agricultural purposes. The main area of application of robots in agriculture today is at the harvesting stage. Emerging applications of robots or drones in agriculture include weed control, [1] [2] [3] cloud seeding, [4] planting seeds, harvesting, environmental monitoring and soil analysis.
Emerging digital technologies have the potential to be game-changers for traditional agricultural practices. The Food and Agriculture Organization of the United Nations has referred to this change as a revolution: "a 'digital agricultural revolution' will be the newest shift which could help ensure agriculture meets the needs of the global population into the future."
Artificial Intelligence for Environment & Sustainability (ARIES) is an international non-profit research project hosted by the Basque Centre for Climate Change (BC3) headquartered in Bilbao, Spain. [1] It was created to integrate scientific computational models for environmental sustainability assessment and policy-making, [2] [3] [4] through ...
As CIO of an agricultural giant with annual sales of $177 billion, Jennifer Hartsock thinks about how the tech tools and capabilities she deploys can help farmers become profitable and sustainable.
The E-agriculture in Action series of publications, by FAO-ITU, that provides guidance on emerging technologies and how it could be used to address some of the challenges in agriculture through documenting case studies. E-agriculture in Action: Big Data for Agriculture [22] E-agriculture in Action: Blockchain for Agriculture [23]
Precision agriculture (PA) is a management strategy that gathers, processes and analyzes temporal, spatial and individual plant and animal data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of ...