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Recent technological and commercial developments make cloud computing an affordable, scalable, and highly-available platform technology. Meanwhile, precision agriculture is showing its potentials by improving agricultural operations through better data-driven decision making. Nevertheless, further development of precision agriculture requires better technology and tools to process data efficiently at a reasonable cost, and to translate the data to better decisions and actions in a field. We developed a framework for cloud-based Decision Support and Automation systems that can acquire data from various sources, synthesize application-specific decisions, and control field devices from the Cloud. A distinctive feature of our framework is its extensible software architecture: decision modules can be added and/or configured for a specific operation. The platform features a device-agnostic frontend that can process incoming data in different formats and semantics. Finally, the platform incorporates software-defined control, a new software design paradigm we proposed to enable versatile and safe control of field devices from a cloud computing platform. An early version of the system has been developed and tested with support from the USDA.
Li Tan (Fri,) studied this question.
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