Abstract: 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.
[1]
Bertrand Meyer.
Tell Less, Say More: The Power of Implicitness
,
1998,
Computer.
[2]
Layuan Li,et al.
Optimal resource provisioning for cloud computing environment
,
2012,
The Journal of Supercomputing.
[3]
Fernando M. V. Ramos,et al.
Software-Defined Networking: A Comprehensive Survey
,
2014,
Proceedings of the IEEE.
[4]
Qin Zhang,et al.
An extensible and integrated software architecture for data analysis and visualization in precision agriculture
,
2012,
2012 IEEE 13th International Conference on Information Reuse & Integration (IRI).
[5]
Marimuthu Palaniswami,et al.
Internet of Things (IoT): A vision, architectural elements, and future directions
,
2012,
Future Gener. Comput. Syst..
[6]
P. Mell,et al.
The NIST Definition of Cloud Computing
,
2011
.